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16.36 Communication Systems Engineering (MIT) 16.36 Communication Systems Engineering (MIT)

Description

16.36 covers the fundamentals of digital communications and networking, including the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking includes multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class are discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications. 16.36 covers the fundamentals of digital communications and networking, including the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking includes multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class are discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications.Subjects

communication systems engineering | communication systems engineering | digital communications | digital communications | networking | networking | information theory | information theory | sampling and quantization | sampling and quantization | modulation | modulation | signal detection | signal detection | system performance | system performance | aerospace communications systems | aerospace communications systems | data networking | data networkingLicense

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See all metadata18.310 Principles of Applied Mathematics (MIT) 18.310 Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.Subjects

sorting algorithms | sorting algorithms | information theory | information theory | coding theory | coding theory | secret codes | secret codes | generating functions | generating functions | linear programming | linear programming | game theory | game theoryLicense

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 metadata18.310 Principles of Applied Mathematics (MIT) 18.310 Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.Subjects

sorting algorithms | sorting algorithms | information theory | information theory | coding theory | coding theory | secret codes | secret codes | generating functions | generating functions | linear programming | linear programming | game theory | game theory | discrete applied mathematics | discrete applied mathematics | mathematical analysis | mathematical analysis | sorting data | sorting data | efficient data storage | efficient data storage | efficient data transmission | efficient data transmission | error correction | error correction | secrecy | secrecy | Fast Fourier Transform | Fast Fourier Transform | network-flow problems | network-flow problems | mathematical economics | mathematical economics | statistics | statistics | probability theory | probability theory | combinatorics | combinatorics | linear algebra | linear algebraLicense

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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Mathematical introduction to neural coding and dynamics. Convolution, correlation, linear systems, Fourier analysis, signal detection theory, probability theory, and information theory. Applications to neural coding, focusing on the visual system. Hodgkin-Huxley and related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission. Mathematical introduction to neural coding and dynamics. Convolution, correlation, linear systems, Fourier analysis, signal detection theory, probability theory, and information theory. Applications to neural coding, focusing on the visual system. Hodgkin-Huxley and related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.Subjects

neural coding | neural coding | dynamics | dynamics | convolution | convolution | correlation | correlation | linear systems | linear systems | Fourier analysis | Fourier analysis | signal detection theory | signal detection theory | probability theory | probability theory | information theory | information theory | neural excitability | neural excitability | stochastic models | stochastic models | ion channels | ion channels | cable theory | cable theory | 9.29 | 9.29 | 8.261 | 8.261License

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See all metadata2.717J Optical Engineering (MIT) 2.717J Optical Engineering (MIT)

Description

This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included. This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included.Subjects

optical methods in engineering and system design | optical methods in engineering and system design | diffraction | statistical optics | holography | and imaging | diffraction | statistical optics | holography | and imaging | Statistical Optics | Inverse Problems (i.e. theory of imaging) | Statistical Optics | Inverse Problems (i.e. theory of imaging) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | Fourier optics | Fourier optics | probability | probability | stochastic processes | stochastic processes | light statistics | light statistics | theory of light coherence | theory of light coherence | van Cittert-Zernicke Theorem | van Cittert-Zernicke Theorem | statistical optics applications | statistical optics applications | inverse problems | inverse problems | information-theoretic views | information-theoretic views | information theory | information theory | 2.717 | 2.717 | MAS.857 | MAS.857License

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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This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission. Visit the Seung Lab Web site. This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission. Visit the Seung Lab Web site.Subjects

neural coding | neural coding | dynamics | dynamics | convolution | convolution | correlation | correlation | linear systems | linear systems | Fourier analysis | Fourier analysis | signal detection theory | signal detection theory | probability theory | probability theory | information theory | information theory | neural excitability | neural excitability | stochastic models | stochastic models | ion channels | ion channels | cable theory | cable theoryLicense

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 metadata16.36 Communication Systems Engineering (MIT) 16.36 Communication Systems Engineering (MIT)

Description

This course will cover fundamentals of digital communications and networking. We will study the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking will include multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class will be discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications. This course will cover fundamentals of digital communications and networking. We will study the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking will include multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class will be discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications.Subjects

digital communications | digital communications | networking | networking | information theory | information theory | sampling | sampling | quantization | quantization | coding | coding | modulation | modulation | signal detection | signal detection | data networking | data networking | multiple access | multiple access | packet transmission | packet transmission | routing | routing | aerospace communication | aerospace communication | aircraft communication | aircraft communication | satellite communication | satellite communication | deep space communication | deep space communication | communication systems haykin | communication systems haykin | computer networks tanenbaum | computer networks tanenbaum | communication systems engineering proakis | communication systems engineering proakis | sampling theorem | sampling theorem | entropy | entropy | signal detection in noise | signal detection in noise | delay models | delay modelsLicense

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 metadata18.310C Principles of Applied Mathematics (MIT) 18.310C Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing. Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing.Subjects

sorting algorithms | sorting algorithms | information theory | information theory | coding theory | coding theory | secret codes | secret codes | generating functions | generating functions | linear programming | linear programming | game theory | game theoryLicense

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 metadataHST.950J Biomedical Computing (MIT) HST.950J Biomedical Computing (MIT)

Description

Analyzes computational needs of clinical medicine reviews systems and approaches that have been used to support those needs, and the relationship between clinical data and gene and protein measurements. Topics: the nature of clinical data; architecture and design of healthcare information systems; privacy and security issues; medical expertsystems; introduction to bioinformatics. Case studies and guest lectures describe contemporary systems and research projects. Term project using large clinical and genomic data sets integrates classroom topics. Analyzes computational needs of clinical medicine reviews systems and approaches that have been used to support those needs, and the relationship between clinical data and gene and protein measurements. Topics: the nature of clinical data; architecture and design of healthcare information systems; privacy and security issues; medical expertsystems; introduction to bioinformatics. Case studies and guest lectures describe contemporary systems and research projects. Term project using large clinical and genomic data sets integrates classroom topics.Subjects

HST.950 | HST.950 | medical informatics | medical informatics | bioinformatics | bioinformatics | developing countries | developing countries | medical data | medical data | clinical data | clinical data | probabilistic models | probabilistic models | graphical models | graphical models | information theory | information theory | decision support | decision support | expert systems | expert systems | personal health records | personal health records | bayesian networks | bayesian networks | bayesian models | bayesian models | health information systems | health information systems | public health informatics | public health informatics | predictive genomics | predictive genomics | patient data privacy | patient data privacyLicense

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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This class teaches the fundamentals of signals and information theory with emphasis on modeling audio/visual messages and physiologically derived signals, and the human source or recipient. Topics include linear systems, difference equations, Z-transforms, sampling and sampling rate conversion, convolution, filtering, modulation, Fourier analysis, entropy, noise, and Shannon's fundamental theorems. Additional topics may include data compression, filter design, and feature detection. The undergraduate subject MAS.160 meets with the two half-semester graduate subjects MAS.510 and MAS.511, but assignments differ. This class teaches the fundamentals of signals and information theory with emphasis on modeling audio/visual messages and physiologically derived signals, and the human source or recipient. Topics include linear systems, difference equations, Z-transforms, sampling and sampling rate conversion, convolution, filtering, modulation, Fourier analysis, entropy, noise, and Shannon's fundamental theorems. Additional topics may include data compression, filter design, and feature detection. The undergraduate subject MAS.160 meets with the two half-semester graduate subjects MAS.510 and MAS.511, but assignments differ.Subjects

audio | audio | visual | visual | video | video | A/V | A/V | digital media | digital media | digital audio | digital audio | digital video | digital video | photography | photography | digitial photography | digitial photography | spectrum | spectrum | Spectrum plot | Spectrum plot | amplitude modulation | amplitude modulation | AM | AM | Fourier series | Fourier series | frequency modulation | frequency modulation | FM | FM | orthogonality | orthogonality | Walsh functions | Walsh functions | basis sets. Sampling theorem | basis sets. Sampling theorem | aliasing | aliasing | reconstruction | reconstruction | FFT | FFT | DFT | DFT | DTFT | DTFT | z-transform | z-transform | IIR | IIR | frequency response | frequency response | filter | filter | filter response | filter response | impulse response | impulse response | noise | noise | communications system | communications system | communications theory | communications theory | information theory | information theory | communication channel | communication channel | coding | coding | error correction | error correction | DSP | DSP | signal processing | signal processing | digital signal processing | digital signal 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 metadataLecture 8: Strategy, Skill, and Chance, Part 1 Lecture 8: Strategy, Skill, and Chance, Part 1

Description

Description: Games contain various skill requirements, chance elements, and information availability, which guide strategy development. Changing the balance between these factors can create very different player experiences. Instructors/speakers: Philip Tan, Jason BegyKeywords: competition, strategy, game theory, roleplaying, vertigo, mimicry, ilinx, sports, alea, gameshows, randomness, games of skill, games of chance, luck, information theory, communication channel, noise, game state, card games, board games, determinism, probability, decision tree, utility, Nash equilibriumTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA) Description: Games contain various skill requirements, chance elements, and information availability, which guide strategy development. Changing the balance between these factors can create very different player experiences. Instructors/speakers: Philip Tan, Jason BegyKeywords: competition, strategy, game theory, roleplaying, vertigo, mimicry, ilinx, sports, alea, gameshows, randomness, games of skill, games of chance, luck, information theory, communication channel, noise, game state, card games, board games, determinism, probability, decision tree, utility, Nash equilibriumTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

competition | competition | strategy | strategy | game theory | game theory | roleplaying | roleplaying | vertigo | vertigo | mimicry | mimicry | ilinx | ilinx | sports | sports | alea | alea | gameshows | gameshows | randomness | randomness | games of skill | games of skill | games of chance | games of chance | luck | luck | information theory | information theory | communication channel | communication channel | noise | noise | game state | game state | card games | card games | board games | board games | determinism | determinism | probability | probability | decision tree | decision tree | utility | utility | Nash equilibrium | Nash equilibriumLicense

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 metadataLecture 9: Strategy, Skill, and Chance, Part 2 Lecture 9: Strategy, Skill, and Chance, Part 2

Description

Description: This lecture reviews the concepts of information flow and uncertainty, analyzing well-known games in these terms. Examples include Scrabble, Go Fish, Mario Kart, Monopoly, chess, poker, War, and Settlers of Catan. Next, students consider feedback loops. Instructors/speakers: Philip Tan, Jason BegyKeywords: complexity, determinism, randomness, uncertainty, strategy, games of skill, games of chance, playtesting, information theory, risk, game state, board games, probability, cybernetics, positive feedback loop, negative feedback loopTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA) Description: This lecture reviews the concepts of information flow and uncertainty, analyzing well-known games in these terms. Examples include Scrabble, Go Fish, Mario Kart, Monopoly, chess, poker, War, and Settlers of Catan. Next, students consider feedback loops. Instructors/speakers: Philip Tan, Jason BegyKeywords: complexity, determinism, randomness, uncertainty, strategy, games of skill, games of chance, playtesting, information theory, risk, game state, board games, probability, cybernetics, positive feedback loop, negative feedback loopTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

complexity | complexity | determinism | determinism | randomness | randomness | uncertainty | uncertainty | strategy | strategy | games of skill | games of skill | games of chance | games of chance | playtesting | playtesting | information theory | information theory | risk | risk | game state | game state | board games | board games | probability | probability | cybernetics | cybernetics | positive feedback loop | positive feedback loop | negative feedback loop | negative feedback loopLicense

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 metadataLecture 30: Clients for Assignment 3 Visit Lecture 30: Clients for Assignment 3 Visit

Description

Description: The 3rd team assignment is to design a simulation for psychiatry residents interacting with agitated patients. Dr. Cezar Cimpeanu and Dr. James Cartreine present an overview of the problem and discuss their research on effective conflict resolution. Instructors/speakers: Philip Tan, Jason Begy, Cezar Cimpeanu, James CartreineKeywords: psychiatry, doctor, violence, simulation, teaching, roleplaying, conflict resolution, assault, narrative, storytelling, NASA, astronaut training, decision tree, information theory, communication channel, isolation, risk assessment, anger management, ethics, mental illness, patientTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA) Description: The 3rd team assignment is to design a simulation for psychiatry residents interacting with agitated patients. Dr. Cezar Cimpeanu and Dr. James Cartreine present an overview of the problem and discuss their research on effective conflict resolution. Instructors/speakers: Philip Tan, Jason Begy, Cezar Cimpeanu, James CartreineKeywords: psychiatry, doctor, violence, simulation, teaching, roleplaying, conflict resolution, assault, narrative, storytelling, NASA, astronaut training, decision tree, information theory, communication channel, isolation, risk assessment, anger management, ethics, mental illness, patientTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

psychiatry | psychiatry | doctor | doctor | violence | violence | simulation | simulation | teaching | teaching | roleplaying | roleplaying | conflict resolution | conflict resolution | assault | assault | narrative | narrative | storytelling | storytelling | NASA | NASA | astronaut training | astronaut training | decision tree | decision tree | information theory | information theory | communication channel | communication channel | isolation | isolation | risk assessment | risk assessment | anger management | anger management | ethics | ethics | mental illness | mental illness | patient | patientLicense

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 metadata18.310C Principles of Applied Mathematics (MIT) 18.310C Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing. Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing.Subjects

sorting algorithms | sorting algorithms | information theory | information theory | coding theory | coding theory | secret codes | secret codes | generating functions | generating functions | linear programming | linear programming | game theory | game theoryLicense

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 metadataLecture 8: Strategy, Skill, and Chance, Part 1

Description

Description: Games contain various skill requirements, chance elements, and information availability, which guide strategy development. Changing the balance between these factors can create very different player experiences. Instructors/speakers: Philip Tan, Jason BegyKeywords: competition, strategy, game theory, roleplaying, vertigo, mimicry, ilinx, sports, alea, gameshows, randomness, games of skill, games of chance, luck, information theory, communication channel, noise, game state, card games, board games, determinism, probability, decision tree, utility, Nash equilibriumTranscript: PDF (English - US)Subtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

competition | strategy | game theory | roleplaying | vertigo | mimicry | ilinx | sports | alea | gameshows | randomness | games of skill | games of chance | luck | information theory | communication channel | noise | game state | card games | board games | determinism | probability | decision tree | utility | Nash equilibriumLicense

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 metadataLecture 9: Strategy, Skill, and Chance, Part 2

Description

Description: This lecture reviews the concepts of information flow and uncertainty, analyzing well-known games in these terms. Examples include Scrabble, Go Fish, Mario Kart, Monopoly, chess, poker, War, and Settlers of Catan. Next, students consider feedback loops. Instructors/speakers: Philip Tan, Jason BegyKeywords: complexity, determinism, randomness, uncertainty, strategy, games of skill, games of chance, playtesting, information theory, risk, game state, board games, probability, cybernetics, positive feedback loop, negative feedback loopTranscript: PDF (English - US)Subtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

complexity | determinism | randomness | uncertainty | strategy | games of skill | games of chance | playtesting | information theory | risk | game state | board games | probability | cybernetics | positive feedback loop | negative feedback loopLicense

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 metadataLecture 30: Clients for Assignment 3 Visit

Description

Description: The 3rd team assignment is to design a simulation for psychiatry residents interacting with agitated patients. Dr. Cezar Cimpeanu and Dr. James Cartreine present an overview of the problem and discuss their research on effective conflict resolution. Instructors/speakers: Philip Tan, Jason Begy, Cezar Cimpeanu, James CartreineKeywords: psychiatry, doctor, violence, simulation, teaching, roleplaying, conflict resolution, assault, narrative, storytelling, NASA, astronaut training, decision tree, information theory, communication channel, isolation, risk assessment, anger management, ethics, mental illness, patientTranscript: PDF (English - US)Subtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

psychiatry | doctor | violence | simulation | teaching | roleplaying | conflict resolution | assault | narrative | storytelling | NASA | astronaut training | decision tree | information theory | communication channel | isolation | risk assessment | anger management | ethics | mental illness | patientLicense

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 metadata2.717J Optical Engineering (MIT)

Description

This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included.Subjects

optical methods in engineering and system design | diffraction | statistical optics | holography | and imaging | Statistical Optics | Inverse Problems (i.e. theory of imaging) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | Fourier optics | probability | stochastic processes | light statistics | theory of light coherence | van Cittert-Zernicke Theorem | statistical optics applications | inverse problems | information-theoretic views | information theory | 2.717 | MAS.857License

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 metadata18.310C Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world. This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing.Subjects

sorting algorithms | information theory | coding theory | secret codes | generating functions | linear programming | game theoryLicense

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 metadata16.36 Communication Systems Engineering (MIT)

Description

16.36 covers the fundamentals of digital communications and networking, including the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking includes multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class are discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications.Subjects

communication systems engineering | digital communications | networking | information theory | sampling and quantization | modulation | signal detection | system performance | aerospace communications systems | data networkingLicense

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 metadata18.310 Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.Subjects

sorting algorithms | information theory | coding theory | secret codes | generating functions | linear programming | game theoryLicense

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 metadata18.310 Principles of Applied Mathematics (MIT)

Description

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.Subjects

sorting algorithms | information theory | coding theory | secret codes | generating functions | linear programming | game theory | discrete applied mathematics | mathematical analysis | sorting data | efficient data storage | efficient data transmission | error correction | secrecy | Fast Fourier Transform | network-flow problems | mathematical economics | statistics | probability theory | combinatorics | linear algebraLicense

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 metadata9.29J Introduction to Computational Neuroscience (MIT)

Description

Mathematical introduction to neural coding and dynamics. Convolution, correlation, linear systems, Fourier analysis, signal detection theory, probability theory, and information theory. Applications to neural coding, focusing on the visual system. Hodgkin-Huxley and related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.Subjects

neural coding | dynamics | convolution | correlation | linear systems | Fourier analysis | signal detection theory | probability theory | information theory | neural excitability | stochastic models | ion channels | cable theory | 9.29 | 8.261License

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 metadata2.717J Optical Engineering (MIT)

Description

This course concerns the theory and practice of optical methods in engineering and system design, with an emphasis on diffraction, statistical optics, holography, and imaging. It provides the engineering methodology skills necessary to incorporate optical components in systems serving diverse areas such as precision engineering and metrology, bio-imaging, and computing (sensors, data storage, communication in multi-processor systems). Experimental demonstrations and a design project are included.Subjects

optical methods in engineering and system design | diffraction | statistical optics | holography | and imaging | Statistical Optics | Inverse Problems (i.e. theory of imaging) | applications in precision engineering and metrology | bio-imaging | and computing (sensors | data storage | communication in multi-processor systems) | Fourier optics | probability | stochastic processes | light statistics | theory of light coherence | van Cittert-Zernicke Theorem | statistical optics applications | inverse problems | information-theoretic views | information theory | 2.717 | MAS.857License

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 metadata16.36 Communication Systems Engineering (MIT)

Description

This course will cover fundamentals of digital communications and networking. We will study the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking will include multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class will be discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications.Subjects

digital communications | networking | information theory | sampling | quantization | coding | modulation | signal detection | data networking | multiple access | packet transmission | routing | aerospace communication | aircraft communication | satellite communication | deep space communication | communication systems haykin | computer networks tanenbaum | communication systems engineering proakis | sampling theorem | entropy | signal detection in noise | delay modelsLicense

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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