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Description
The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering. The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering.Subjects
comonent analysis | comonent analysis | PCA | PCA | ICA | ICA | fourier analysis | fourier analysis | vision | vision | machine vision | machine vision | pattern matching | pattern matching | pattern analysis | pattern analysis | pattern recognition | pattern recognition | scene analysis | scene analysis | tracking | tracking | feature extraction | feature extraction | color | color | color space | color space | clustering | clustering | bayesian decisions | bayesian decisions | gesture recognition | gesture recognition | action recognition | action recognition | image processing | image processing | image formation | image formation | density estimation | density estimation | classification | classification | morphable models | morphable models | component analysis | component analysisLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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The course is directed towards advanced undergraduate and beginning graduate students. It will focus on applications of pattern recognition techniques to problems of machine vision.The topics covered in the course include:Overview of problems of machine vision and pattern classificationImage formation and processingFeature extraction from imagesBiological object recognitionBayesian decision theoryClustering The course is directed towards advanced undergraduate and beginning graduate students. It will focus on applications of pattern recognition techniques to problems of machine vision.The topics covered in the course include:Overview of problems of machine vision and pattern classificationImage formation and processingFeature extraction from imagesBiological object recognitionBayesian decision theoryClusteringSubjects
pattern recognition | pattern recognition | machine vision | machine vision | pattern classification | pattern classification | Image formation | Image formation | processing | processing | feature extraction | feature extraction | Biological object recognition | Biological object recognition | Bayesian Decision Theory | Bayesian Decision Theory | Clustering | ClusteringLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadataMAS.622J Pattern Recognition and Analysis (MIT) MAS.622J Pattern Recognition and Analysis (MIT)
Description
This class deals with the fundamentals of characterizing and recognizing patterns and features of interest in numerical data. We discuss the basic tools and theory for signal understanding problems with applications to user modeling, affect recognition, speech recognition and understanding, computer vision, physiological analysis, and more. We also cover decision theory, statistical classification, maximum likelihood and Bayesian estimation, nonparametric methods, unsupervised learning and clustering. Additional topics on machine and human learning from active research are also talked about in the class. This class deals with the fundamentals of characterizing and recognizing patterns and features of interest in numerical data. We discuss the basic tools and theory for signal understanding problems with applications to user modeling, affect recognition, speech recognition and understanding, computer vision, physiological analysis, and more. We also cover decision theory, statistical classification, maximum likelihood and Bayesian estimation, nonparametric methods, unsupervised learning and clustering. Additional topics on machine and human learning from active research are also talked about in the class.Subjects
MAS.622 | MAS.622 | 1.126 | 1.126 | pattern recognition | pattern recognition | feature detection | feature detection | classification | classification | probability theory | probability theory | pattern analysis | pattern analysis | conditional probability | conditional probability | bayes rule | bayes rule | random vectors | decision theory | random vectors | decision theory | ROC curves | ROC curves | likelihood ratio test | likelihood ratio test | fisher discriminant | fisher discriminant | template-based recognition | template-based recognition | feature extraction | feature extraction | eigenvector and multilinear analysis | eigenvector and multilinear analysis | linear discriminant | linear discriminant | perceptron learning | perceptron learning | optimization by gradient descent | optimization by gradient descent | support vecotr machines | support vecotr machines | K-nearest-neighbor classification | K-nearest-neighbor classification | parzen estimation | parzen estimation | unsupervised learning | unsupervised learning | clustering | clustering | vector quantization | vector quantization | K-means | K-means | Expectation-Maximization | Expectation-Maximization | Hidden markov models | Hidden markov models | viterbi algorithm | viterbi algorithm | Baum-Welch algorithm | Baum-Welch algorithm | linear dynamical systems | linear dynamical systems | Kalman filtering | Kalman filtering | Bayesian networks | Bayesian networks | decision trees | decision trees | reinforcement learning | reinforcement learning | genetic algorithms | genetic algorithmsLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata9.913 Pattern Recognition for Machine Vision (MIT)
Description
The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering.Subjects
comonent analysis | PCA | ICA | fourier analysis | vision | machine vision | pattern matching | pattern analysis | pattern recognition | scene analysis | tracking | feature extraction | color | color space | clustering | bayesian decisions | gesture recognition | action recognition | image processing | image formation | density estimation | classification | morphable models | component analysisLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata9.036 The Visual System (MIT) 9.036 The Visual System (MIT)
Description
In this seminar anatomical, neurophysiological, imaging and behavioral research will be examined in an attempt to gain a better understanding of how information is processed in the primate visual system. The first five sessions provide an overview of the functional and structural organization of the visual system with a critical examination of some of the basic issues in the field. Thereafter the emphasis will shift to the question of how various aspects of the visual scene are processed in the visual system. We will study color vision, adaptation, the role of eye movements in carrying out visual analysis, motion perception, depth perception and pattern perception. In this seminar anatomical, neurophysiological, imaging and behavioral research will be examined in an attempt to gain a better understanding of how information is processed in the primate visual system. The first five sessions provide an overview of the functional and structural organization of the visual system with a critical examination of some of the basic issues in the field. Thereafter the emphasis will shift to the question of how various aspects of the visual scene are processed in the visual system. We will study color vision, adaptation, the role of eye movements in carrying out visual analysis, motion perception, depth perception and pattern perception.Subjects
anatomical | anatomical | neurophysiological | neurophysiological | imaging | imaging | behavior | behavior | functional | functional | structural organization | structural organization | visual scene | visual scene | processing | processing | visual system | visual system | color vision | color vision | adaptation | adaptation | eye movements | eye movements | motion perception | motion perception | depth perception | depth perception | pattern perception | pattern perception | visual analysis | visual analysisLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata9.65 Cognitive Processes (MIT) 9.65 Cognitive Processes (MIT)
Description
An introduction to human information processing and learning; topics include the nature of mental representation and processing; the architecture of memory; pattern recognition; attention; imagery and mental codes; concepts and prototypes; reasoning and problem solving. An introduction to human information processing and learning; topics include the nature of mental representation and processing; the architecture of memory; pattern recognition; attention; imagery and mental codes; concepts and prototypes; reasoning and problem solving.Subjects
human | human | information processing | information processing | learning | learning | mental representation | mental representation | processing | processing | architecture of memory | architecture of memory | pattern recognition | pattern recognition | attention | attention | imagery | imagery | mental codes | mental codes | concepts | concepts | prototypes | prototypes | reasoning | reasoning | problem solving | problem solvingLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata9.18 Developmental Neurobiology (MIT) 9.18 Developmental Neurobiology (MIT)
Description
This course considers molecular control of neural specification, formation of neuronal connections, construction of neural systems, and the contributions of experience to shaping brain structure and function. Topics include: neural induction and pattern formation, cell lineage and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development and critical periods, development of behavior. This course considers molecular control of neural specification, formation of neuronal connections, construction of neural systems, and the contributions of experience to shaping brain structure and function. Topics include: neural induction and pattern formation, cell lineage and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development and critical periods, development of behavior.Subjects
molecular | molecular | neural specification | neural specification | ormation of neuronal connections | ormation of neuronal connections | construction of neural systems | construction of neural systems | experience | experience | formation of neuronal connections | formation of neuronal connections | neural induction | neural induction | pattern formation | pattern formation | cell lineage | cell lineage | fate determination | fate determination | neuronal migration | neuronal migration | axon guidance | axon guidance | synapse formation | synapse formation | stabilization | stabilization | activity-dependent development | activity-dependent development | critical periods | critical periods | development | developmentLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.170 Laboratory in Software Engineering (MIT) 6.170 Laboratory in Software Engineering (MIT)
Description
This course is a a core electrical engineering computer science subject at MIT. It introduces concepts and techniques relevant to the production of large software systems. Students are taught a programming method based on the recognition and description of useful abstractions. Topics include: modularity; specification; data abstraction; object modeling; design patterns; and testing. Several programming projects of varying size undertaken by students working individually and in groups. This course is a a core electrical engineering computer science subject at MIT. It introduces concepts and techniques relevant to the production of large software systems. Students are taught a programming method based on the recognition and description of useful abstractions. Topics include: modularity; specification; data abstraction; object modeling; design patterns; and testing. Several programming projects of varying size undertaken by students working individually and in groups.Subjects
software development | modularity | specification; data abstraction; object modeling | design patterns | software development | modularity | specification; data abstraction; object modeling | design patterns | modularity | modularity | software development | software development | specification | specification | data abstraction | data abstraction | software design | software design | object modeling | object modeling | software testing | software testing | large systems | large systemsLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata11.304J Site and Urban Systems Planning (MIT) 11.304J Site and Urban Systems Planning (MIT)
Description
The Site and Urban Systems Planning course provides a unique opportunity to engage in the exploration, utilization and critical assessment of new multi-layered manipulative simulation interfaces. Developed by the Tangible Media Group at the Media Lab, these platforms combine and update digital and tangible data in ways that promise to enhance design and planning processes and communication with the public. By testing and applying these platforms, as well as traditional methods, we will be able to learn various approaches involved in evaluating and planning sites.These approaches include:Understanding spatial as well as temporal relationships between individual site factors and local or regional context.Identifying basic relationships between natural and cultural processes and how they infl The Site and Urban Systems Planning course provides a unique opportunity to engage in the exploration, utilization and critical assessment of new multi-layered manipulative simulation interfaces. Developed by the Tangible Media Group at the Media Lab, these platforms combine and update digital and tangible data in ways that promise to enhance design and planning processes and communication with the public. By testing and applying these platforms, as well as traditional methods, we will be able to learn various approaches involved in evaluating and planning sites.These approaches include:Understanding spatial as well as temporal relationships between individual site factors and local or regional context.Identifying basic relationships between natural and cultural processes and how they inflSubjects
site planning | site planning | natural systems | natural systems | digital planning | digital planning | site analysis | site analysis | evaluation and selection | evaluation and selection | spatial organization and programming | spatial organization and programming | analysis of surface runoff | analysis of surface runoff | utility systems | utility systems | design of circulation | design of circulation | parking and subdivision patterns | parking and subdivision patterns | street layouts | street layouts | 11.304 | 11.304License
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata8.592 Statistical Physics in Biology (MIT) 8.592 Statistical Physics in Biology (MIT)
Description
Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; Considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.Technical RequirementsAny number of biological sequence comparison software tools can be used to import the .fna files found on this course site. Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; Considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.Technical RequirementsAny number of biological sequence comparison software tools can be used to import the .fna files found on this course site.Subjects
Bioinformatics | Bioinformatics | DNA | DNA | gene finding | gene finding | sequence comparison | sequence comparison | phylogenetic trees | phylogenetic trees | biopolymers | biopolymers | DNA double helix | DNA double helix | secondary structure of RNA | secondary structure of RNA | protein folding | protein folding | protein motors | membranes | protein motors | membranes | cellular networks | cellular networks | neural networks | neural networks | evolution | evolution | statistical physics | statistical physics | molecular biology | molecular biology | deoxyribonucleic acid | deoxyribonucleic acid | genes | genes | genetics | genetics | gene sequencing | gene sequencing | phylogenetics | phylogenetics | double helix | double helix | RNA | RNA | ribonucleic acid | ribonucleic acid | force | force | motion | motion | packaging | packaging | protein motors | protein motors | membranes | membranes | biochemistry | biochemistry | genome | genome | optimization | optimization | partitioning | partitioning | pattern recognition | pattern recognition | collective behavior | collective behaviorLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.189 Multicore Programming Primer (MIT) 6.189 Multicore Programming Primer (MIT)
Description
Includes audio/video content: AV lectures, AV special element video, AV special element video. The course serves as an introductory course in parallel programming. It offers a series of lectures on parallel programming concepts as well as a group project providing hands-on experience with parallel programming. The students will have the unique opportunity to use the cutting-edge PLAYSTATION 3 development platform as they learn how to design and implement exciting applications for multicore architectures. At the end of the course, students will have an understanding of: Fundamental design philosophies that multicore architectures address. Parallel programming philosophies and emerging best practices. This course is offered during the Independent Activities Period (IAP), which is a specia Includes audio/video content: AV lectures, AV special element video, AV special element video. The course serves as an introductory course in parallel programming. It offers a series of lectures on parallel programming concepts as well as a group project providing hands-on experience with parallel programming. The students will have the unique opportunity to use the cutting-edge PLAYSTATION 3 development platform as they learn how to design and implement exciting applications for multicore architectures. At the end of the course, students will have an understanding of: Fundamental design philosophies that multicore architectures address. Parallel programming philosophies and emerging best practices. This course is offered during the Independent Activities Period (IAP), which is a speciaSubjects
multicore architectures | multicore architectures | parallel programming patterns | parallel programming patterns | Sony PlayStation 3 | Sony PlayStation 3 | competition | competitionLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata11.949 City Visions: Past and Future (MIT) 11.949 City Visions: Past and Future (MIT)
Description
This class is intended to introduce students to understandings of the city generated from both social science literature and the field of urban design. The first part of the course examines literature on the history and theory of the city. Among other factors, it pays special attention to the larger territorial settings in which cities emerged and developed (ranging from the global to the national to the regional context) and how these affected the nature, character, and functioning of cities and the lives of their inhabitants. The remaining weeks focus more explicitly on the theory and practice of design visions for the city, the latter in both utopian and realized form. One of our aims will be to assess the conditions under which a variety of design visions were conceived, and to as This class is intended to introduce students to understandings of the city generated from both social science literature and the field of urban design. The first part of the course examines literature on the history and theory of the city. Among other factors, it pays special attention to the larger territorial settings in which cities emerged and developed (ranging from the global to the national to the regional context) and how these affected the nature, character, and functioning of cities and the lives of their inhabitants. The remaining weeks focus more explicitly on the theory and practice of design visions for the city, the latter in both utopian and realized form. One of our aims will be to assess the conditions under which a variety of design visions were conceived, and to asSubjects
understandings of the city | understandings of the city | social science literature and the field of urban design | social science literature and the field of urban design | literature on the history and theory of the city | literature on the history and theory of the city | larger territorial settings | larger territorial settings | nature | character | and functioning of cities | nature | character | and functioning of cities | lives of inhabitants | lives of inhabitants | theory and practice of design visions for the city | theory and practice of design visions for the city | utopian | utopian | utopian and realized form | utopian and realized form | patterns of territorial ?nestedness? | patterns of territorial ?nestedness? | future prospects of cities | future prospects of cities | territory | territory | cities | cities | context | context | local | local | national | national | global | global | urban settings | urban settings | city design | city design | social justice | social justice | politics of change | politics of change | urban design | urban design | history | history | theory | theory | territorial settings | territorial settings | urbanites | urbanites | city dwellers | city dwellers | inhabitants | inhabitants | nestedness | nestedness | regional | regional | imperial | imperial | politics | politics | sociology | sociologyLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.345 Automatic Speech Recognition (MIT) 6.345 Automatic Speech Recognition (MIT)
Description
Includes audio/video content: AV special element audio. 6.345 introduces students to the rapidly developing field of automatic speech recognition. Its content is divided into three parts. Part I deals with background material in the acoustic theory of speech production, acoustic-phonetics, and signal representation. Part II describes algorithmic aspects of speech recognition systems including pattern classification, search algorithms, stochastic modelling, and language modelling techniques. Part III compares and contrasts the various approaches to speech recognition, and describes advanced techniques used for acoustic-phonetic modelling, robust speech recognition, speaker adaptation, processing paralinguistic information, speech understanding, and multimodal processing. Includes audio/video content: AV special element audio. 6.345 introduces students to the rapidly developing field of automatic speech recognition. Its content is divided into three parts. Part I deals with background material in the acoustic theory of speech production, acoustic-phonetics, and signal representation. Part II describes algorithmic aspects of speech recognition systems including pattern classification, search algorithms, stochastic modelling, and language modelling techniques. Part III compares and contrasts the various approaches to speech recognition, and describes advanced techniques used for acoustic-phonetic modelling, robust speech recognition, speaker adaptation, processing paralinguistic information, speech understanding, and multimodal processing.Subjects
speech recognition | speech recognition | automatic speech recognition | automatic speech recognition | acoustic theory | acoustic theory | speech production | speech production | acoustic-phonetics | acoustic-phonetics | signal representation | signal representation | pattern classification | pattern classification | search algorithms | search algorithms | stochastic modelling | stochastic modelling | language modelling | language modelling | speaker adaptation | speaker adaptation | paralinguistic information | paralinguistic information | speech understanding | speech understanding | multimodal processing | multimodal processingLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.005 Elements of Software Construction (MIT) 6.005 Elements of Software Construction (MIT)
Description
This course introduces fundamental principles and techniques of software development. Students learn how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; state machines; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. The course includes weekly programming exercises and two substantial group projects. This course introduces fundamental principles and techniques of software development. Students learn how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; state machines; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. The course includes weekly programming exercises and two substantial group projects.Subjects
software development | software development | specifications | specifications | invariants | invariants | state machines | state machines | test-driven development | test-driven development | design patterns | design patterns | object-oriented programming | object-oriented programming | concurrent programming | concurrent programming | functional programming | functional programmingLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadataDescription
This course covers concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Substantial weekly programming assignments are an integral part of the subject. There will be extensive programming assignments, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or some other "functional" language. This course covers concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Substantial weekly programming assignments are an integral part of the subject. There will be extensive programming assignments, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or some other "functional" language.Subjects
Scheme | Scheme | symbolic programming | symbolic programming | additive systems | additive systems | generic operations | generic operations | language layers | language layers | pattern-directed invocation | pattern-directed invocation | searching | searching | amb | amb | backtracking | backtracking | propagation systems | propagation systems | constraints | constraints | truth maintenance | truth maintenance | continuations | continuations | structure and interpretation of computer programs | structure and interpretation of computer programsLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.170 Laboratory in Software Engineering (MIT) 6.170 Laboratory in Software Engineering (MIT)
Description
This course introduces concepts and techniques relevant to the production of large software systems. Students are taught a programming method based on the recognition and description of useful abstractions. Topics include modularity, specification, data abstraction, object modeling, design patterns, and testing. Students complete several programming projects of varying size, working individually and in groups. Students are now introduced to software engineering in 6.005 Elements of Software Construction, which is available on OCW in two versions, as taught in Fall 2008 and Fall 2011. This course introduces concepts and techniques relevant to the production of large software systems. Students are taught a programming method based on the recognition and description of useful abstractions. Topics include modularity, specification, data abstraction, object modeling, design patterns, and testing. Students complete several programming projects of varying size, working individually and in groups. Students are now introduced to software engineering in 6.005 Elements of Software Construction, which is available on OCW in two versions, as taught in Fall 2008 and Fall 2011.Subjects
software engineering | software engineering | modularity | modularity | specification | specification | data abstraction | data abstraction | object modeling | object modeling | design patterns | design patterns | testing | testing | Java programming | Java programmingLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.541J Speech Communication (MIT) 6.541J Speech Communication (MIT)
Description
6.541J surveys the structural properties of natural languages, with special emphasis on the sound pattern. Topics covered include: representation of the lexicon; physiology of speech production; articulatory phonetics; acoustical theory of speech production; acoustical and articulatory descriptions of phonetic features and of prosodic aspects of speech; perception of speech; models of lexical access and of speech production and planning; and applications to recognition and generation of speech by machine, and to the study of speech disorders. 6.541J surveys the structural properties of natural languages, with special emphasis on the sound pattern. Topics covered include: representation of the lexicon; physiology of speech production; articulatory phonetics; acoustical theory of speech production; acoustical and articulatory descriptions of phonetic features and of prosodic aspects of speech; perception of speech; models of lexical access and of speech production and planning; and applications to recognition and generation of speech by machine, and to the study of speech disorders.Subjects
speech communication | speech communication | natural languages | natural languages | sound patterns | sound patterns | lexicons | lexicons | speech production | speech production | articulatory phonetics | articulatory phonetics | acoustical theory | acoustical theory | phonetic features | phonetic features | prosodic aspects of speech | prosodic aspects of speech | lexical access | lexical access | speech recognition | speech recognition | speech generation | speech generation | speech disorders | speech disorders | 6.541 | 6.541 | 24.968 | 24.968 | HST.710 | HST.710License
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata6.973 Organic Optoelectronics (MIT) 6.973 Organic Optoelectronics (MIT)
Description
The course examines optical and electronic processes in organic molecules and polymers that govern the behavior of practical organic optoelectronic devices. Electronic structure of a single organic molecule is used as a guide to the electronic behavior of organic aggregate structures. Emphasis is placed on the use of organic thin films in active organic devices including organic LEDs, solar cells, photodetectors, transistors, chemical sensors, memory cells, electrochromic devices, as well as xerography and organic non-linear optics. How to reach the ultimate miniaturization limit of molecular electronics and related nanoscale patterning techniques of organic materials will also be discussed. The class encompasses three laboratory sessions during which the students will practice the use of The course examines optical and electronic processes in organic molecules and polymers that govern the behavior of practical organic optoelectronic devices. Electronic structure of a single organic molecule is used as a guide to the electronic behavior of organic aggregate structures. Emphasis is placed on the use of organic thin films in active organic devices including organic LEDs, solar cells, photodetectors, transistors, chemical sensors, memory cells, electrochromic devices, as well as xerography and organic non-linear optics. How to reach the ultimate miniaturization limit of molecular electronics and related nanoscale patterning techniques of organic materials will also be discussed. The class encompasses three laboratory sessions during which the students will practice the use ofSubjects
organic optoelectronics | organic optoelectronics | optical | optical | electronic | electronic | polymers | polymers | organic thin films | organic thin films | organic LEDs | organic LEDs | solar cells | solar cells | photodetectors | photodetectors | transistors | transistors | chemical sensors | chemical sensors | memory cells | memory cells | electrochromic devices | electrochromic devices | xerography | xerography | organic non-linear optics | organic non-linear optics | miniaturization limit | miniaturization limit | molecular electronics | molecular electronics | nanoscale patterning | nanoscale patterning | vacuum organic deposition | vacuum organic deposition | non-vacuum organic deposition | non-vacuum organic depositionLicense
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See all metadata6.637 Optical Signals, Devices, and Systems (MIT) 6.637 Optical Signals, Devices, and Systems (MIT)
Description
6.637 covers the fundamentals of optical signals and modern optical devices and systems from a practical point of view. Its goal is to help students develop a thorough understanding of the underlying physical principles such that device and system design and performance can be predicted, analyzed, and understood. Most optical systems involve the use of one or more of the following: sources (e.g., lasers and light-emitting diodes), light modulation components (e.g., liquid-crystal light modulators), transmission media (e.g., free space or fibers), photodetectors (e.g., photodiodes, photomultiplier tubes), information storage devices (e.g., optical disk), processing systems (e.g., imaging and spatial filtering systems) and displays (LCOS microdisplays). These are the topics covered by this 6.637 covers the fundamentals of optical signals and modern optical devices and systems from a practical point of view. Its goal is to help students develop a thorough understanding of the underlying physical principles such that device and system design and performance can be predicted, analyzed, and understood. Most optical systems involve the use of one or more of the following: sources (e.g., lasers and light-emitting diodes), light modulation components (e.g., liquid-crystal light modulators), transmission media (e.g., free space or fibers), photodetectors (e.g., photodiodes, photomultiplier tubes), information storage devices (e.g., optical disk), processing systems (e.g., imaging and spatial filtering systems) and displays (LCOS microdisplays). These are the topics covered by thisSubjects
optical | optical | optical signals | optical signals | optical devices | optical devices | transmission | transmission | detection | detection | storage | storage | processing | processing | display | display | electromagnetic waves | electromagnetic waves | diffraction | diffraction | holography | holography | lasers | lasers | LEDs | LEDs | spatial light modulation | spatial light modulation | display technologies | display technologies | optical waveguides | optical waveguides | fiberoptic communication | fiberoptic communication | thermal photodetector | thermal photodetector | quantum photodetector | quantum photodetector | optical storage media | optical storage media | disks | disks | 3-D holographic material | 3-D holographic material | coherent optical processor | coherent optical processor | incoherent optical processor | incoherent optical processor | Fourier optics | Fourier optics | acousto-optics | acousto-optics | optoelectronic neural networks | optoelectronic neural networks | optical interconnection device technologies | optical interconnection device technologies | image processing | image processing | pattern recognition | pattern recognition | radar systems | radar systems | adaptive optical systems | adaptive optical systems | 6.161 | 6.161License
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In this course, we will explore the specific ways by which microbes defeat our immune system and the molecular mechanisms that are under attack (phagocytosis, the ubiquitin/proteasome pathway, MHC I/II antigen presentation). Through our discussion and dissection of the primary research literature, we will explore aspects of host-pathogen interactions. We will particularly emphasize the experimental techniques used in the field and how to read and understand research data. Technological advances in the fight against microbes will also be discussed, with specific examples. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about In this course, we will explore the specific ways by which microbes defeat our immune system and the molecular mechanisms that are under attack (phagocytosis, the ubiquitin/proteasome pathway, MHC I/II antigen presentation). Through our discussion and dissection of the primary research literature, we will explore aspects of host-pathogen interactions. We will particularly emphasize the experimental techniques used in the field and how to read and understand research data. Technological advances in the fight against microbes will also be discussed, with specific examples. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn aboutSubjects
HIV | HIV | mycobacterium tuberculosis | mycobacterium tuberculosis | malaria | malaria | influenza | influenza | immune system | immune system | pathogens | pathogens | viruses | viruses | bacteria | bacteria | parasites | parasites | microbes | microbes | phagocytosis | phagocytosis | ubiquitin/proteasome pathway | ubiquitin/proteasome pathway | MHC I/II antigen presentation | MHC I/II antigen presentation | Salmonella | Salmonella | pathogen-associated molecular patterns | pathogen-associated molecular patterns | PAMP | PAMP | Toll-like receptors | Toll-like receptors | TLR | TLR | Vaccinia virus | Vaccinia virus | Proteasome | Proteasome | Ubiquitin; deubiquinating enzymes | Ubiquitin; deubiquinating enzymes | DUB | DUB | Herpes simplex virus | Herpes simplex virus | HSV | HSV | Yersinia | Yersinia | viral budding | viral budding | Human cytomegalovirus | Human cytomegalovirus | HCMV | HCMV | Histocompatiblity | Histocompatiblity | AIDS | AIDS | Kaposi Sarcoma-Associated Herpes virus | Kaposi Sarcoma-Associated Herpes virus | Mixoma virus | Mixoma virus | Epstein Barr virus | Epstein Barr virus | EBV | EBV | Burkitt?s B cell lymphoma | Burkitt?s B cell lymphomaLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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In this course, we will address how transcriptional regulators both prohibit and drive differentiation during the course of development. How does a stem cell know when to remain a stem cell and when to become a specific cell type? Are there global differences in the way the genome is read in multipotent and terminally differentiated cells? We will explore how stem cell pluripotency is preserved, how master regulators of cell-fate decisions execute developmental programs, and how chromatin regulators control undifferentiated versus differentiated states. Additionally, we will discuss how aberrant regulation of transcriptional regulators produces disorders such as developmental defects and cancer.This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at In this course, we will address how transcriptional regulators both prohibit and drive differentiation during the course of development. How does a stem cell know when to remain a stem cell and when to become a specific cell type? Are there global differences in the way the genome is read in multipotent and terminally differentiated cells? We will explore how stem cell pluripotency is preserved, how master regulators of cell-fate decisions execute developmental programs, and how chromatin regulators control undifferentiated versus differentiated states. Additionally, we will discuss how aberrant regulation of transcriptional regulators produces disorders such as developmental defects and cancer.This course is one of many Advanced Undergraduate Seminars offered by the Biology Department atSubjects
blueprint of life | blueprint of life | transcription | transcription | stem cells | stem cells | differentiation | differentiation | human tissues | human tissues | tissue regeneration | tissue regeneration | human disease | human disease | RNA and protein expression patterns | RNA and protein expression patterns | transcriptional regulation | transcriptional regulation | specialized gene expression programs | specialized gene expression programs | genome | genome | multipotent | multipotent | terminally differentiated | terminally differentiated | pluripotency | pluripotency | master regulators | master regulators | chromatin regulators | chromatin regulators | developmental defects | developmental defects | cancer | cancerLicense
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See all metadata8.591J Systems Biology (MIT) 8.591J Systems Biology (MIT)
Description
This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell co This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell coSubjects
molecular systems biology | molecular systems biology | constructing and modeling of genetic networks | constructing and modeling of genetic networks | control theory and genetic networks | control theory and genetic networks | ambda phage as a genetic switch | ambda phage as a genetic switch | synthetic genetic switches | synthetic genetic switches | bacterial chemotaxis | bacterial chemotaxis | genetic oscillators | genetic oscillators | circadian rhythms | circadian rhythms | cellular systems biology | cellular systems biology | reaction diffusion equations | reaction diffusion equations | local activation and global inhibition models | local activation and global inhibition models | gradient sensing systems | gradient sensing systems | center finding networks | center finding networks | developmental systems biology | developmental systems biology | general pattern formation models | general pattern formation models | modeling cell-cell communication | modeling cell-cell communication | quorum sensing | quorum sensing | models for Drosophilia development | models for Drosophilia development | 8.591 | 8.591 | 7.81 | 7.81License
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata9.916 Special Topics: Social Animals (MIT) 9.916 Special Topics: Social Animals (MIT)
Description
Humans are social animals; social demands, both cooperative and competitive, structure our development, our brain and our mind. This course covers social development, social behaviour, social cognition and social neuroscience, in both human and non-human social animals. Topics include altruism, empathy, communication, theory of mind, aggression, power, groups, mating, and morality. Methods include evolutionary biology, neuroscience, cognitive science, social psychology and anthropology. Humans are social animals; social demands, both cooperative and competitive, structure our development, our brain and our mind. This course covers social development, social behaviour, social cognition and social neuroscience, in both human and non-human social animals. Topics include altruism, empathy, communication, theory of mind, aggression, power, groups, mating, and morality. Methods include evolutionary biology, neuroscience, cognitive science, social psychology and anthropology.Subjects
social animals | social animals | social | social | animals | animals | society | society | human society | human society | members | members | community | community | living together | living together | mutual benefit | mutual benefit | people | people | region | region | country | country | world | world | whole | whole | association | association | body | body | individuals | individuals | functional interdependence | functional interdependence | national or cultural identity | national or cultural identity | social solidarity | social solidarity | language or hierarchical organization | language or hierarchical organization | patterns of relationships between individuals sharing a distinctive culture and institutions | patterns of relationships between individuals sharing a distinctive culture and institutions | groups | groups | economic | economic | social or industrial infrastructure | social or industrial infrastructure | made up of a varied collection of individuals | made up of a varied collection of individuals | ethnic groups | ethnic groups | nation state | nation state | broader cultural group | broader cultural group | organized voluntary association of people for religious | organized voluntary association of people for religious | benevolent | benevolent | cultural | cultural | scientific | scientific | political | political | patriotic | patriotic | or other purposes. | or other purposes.License
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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Understanding the brain's remarkable ability for visual object recognition is one of the greatest challenges of brain research. The goal of this course is to provide an overview of key issues of object representation and to survey data from primate physiology and human fMRI that bear on those issues. Topics include the computational problems of object representation, the nature of object representations in the brain, the tolerance and selectivity of those representations, and the effects of attention and learning. Understanding the brain's remarkable ability for visual object recognition is one of the greatest challenges of brain research. The goal of this course is to provide an overview of key issues of object representation and to survey data from primate physiology and human fMRI that bear on those issues. Topics include the computational problems of object representation, the nature of object representations in the brain, the tolerance and selectivity of those representations, and the effects of attention and learning.Subjects
vision | vision | object recognition | object recognition | monkey versus human | monkey versus human | object representations | object representations | fMRI | fMRI | temporal lobe | temporal lobe | visual cortex | visual cortex | neuronal representations | neuronal representations | neurophysiology | neurophysiology | retinal image | retinal image | pattern recognition | pattern recognition | perceptual awareness | perceptual awarenessLicense
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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See all metadata9.18 Developmental Neurobiology (MIT) 9.18 Developmental Neurobiology (MIT)
Description
This course considers molecular control of neural specification, formation of neuronal connections, construction of neural systems, and the contributions of experience to shaping brain structure and function. Topics include: neural induction and pattern formation, cell lineage and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development and critical periods, development of behavior. This course considers molecular control of neural specification, formation of neuronal connections, construction of neural systems, and the contributions of experience to shaping brain structure and function. Topics include: neural induction and pattern formation, cell lineage and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development and critical periods, development of behavior.Subjects
molecular | molecular | neural specification | neural specification | ormation of neuronal connections | ormation of neuronal connections | construction of neural systems | construction of neural systems | experience | experience | formation of neuronal connections | formation of neuronal connections | neural induction | neural induction | pattern formation | pattern formation | cell lineage | cell lineage | fate determination | fate determination | neuronal migration | neuronal migration | axon guidance | axon guidance | synapse formation | synapse formation | stabilization | stabilization | activity-dependent development | activity-dependent development | critical periods | critical periods | development | development | 9.181 | 9.181 | 7.69 | 7.69License
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from
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