Searching for limitations : 14 results found | RSS Feed for this search

1

16.410 Principles of Autonomy and Decision Making (MIT) 16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search trees

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.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

24.119 Mind and Machines (MIT) 24.119 Mind and Machines (MIT)

Description

This course is an introduction to many of the central issues in a branch of philosophy called philosophy of mind. Some of the questions we will discuss include the following. Can computers think? Is the mind an immaterial thing? Or is the mind the brain? Or does the mind stand to the brain as a computer program stands to the hardware? How can creatures like ourselves think thoughts that are "about" things? (For example, we can all think that Aristotle is a philosopher, and in that sense think "about" Aristotle, but what is the explanation of this quite remarkable ability?) Can I know whether your experiences and my experiences when we look at raspberries, fire trucks and stop lights are the same? Can consciousness be given a scientific explanation? This course is an introduction to many of the central issues in a branch of philosophy called philosophy of mind. Some of the questions we will discuss include the following. Can computers think? Is the mind an immaterial thing? Or is the mind the brain? Or does the mind stand to the brain as a computer program stands to the hardware? How can creatures like ourselves think thoughts that are "about" things? (For example, we can all think that Aristotle is a philosopher, and in that sense think "about" Aristotle, but what is the explanation of this quite remarkable ability?) Can I know whether your experiences and my experiences when we look at raspberries, fire trucks and stop lights are the same? Can consciousness be given a scientific explanation?

Subjects

artificial intelligence | artificial intelligence | psychology | psychology | philosophy | philosophy | Turing Machines | Turing Machines | consciousness | consciousness | computer limitations | computer limitations | computation | computation | neurophysiology | neurophysiology | Turing test | Turing test | the analog/digital distinction | the analog/digital distinction | Chinese Room argument | Chinese Room argument | causal efficacy of content | causal efficacy of content | inverted spectrum | inverted spectrum | mental representation | mental representation | procedural semantics | procedural semantics | connectionism | connectionism

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.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

16.410 Principles of Autonomy and Decision Making (MIT) 16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search trees

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.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

24.119 Mind and Machines (MIT) 24.119 Mind and Machines (MIT)

Description

This course is an introduction to many of the central issues in the philosophy of mind, with an emphasis on consciousness and the mind-body problem. This course is an introduction to many of the central issues in the philosophy of mind, with an emphasis on consciousness and the mind-body problem.

Subjects

artificial intelligence | artificial intelligence | psychology | psychology | philosophy | philosophy | turning machines | turning machines | consciousness | consciousness | computer limitations | computer limitations | computations | computations | neurophysiology | neurophysiology | Turing test | Turing test | the analog/digital distinction | the analog/digital distinction | Chinese Room argument | Chinese Room argument | causal efficacy of content | causal efficacy of content | inverted spectrum | inverted spectrum | mental representation | mental representation | procedural semantics | procedural semantics | connectionism | connectionism

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.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.774 Physics of Microfabrication: Front End Processing (MIT) 6.774 Physics of Microfabrication: Front End Processing (MIT)

Description

Includes audio/video content: AV lectures. This course is offered to graduates and focuses on understanding the fundamental principles of the "front-end" processes used in the fabrication of devices for silicon integrated circuits. This includes advanced physical models and practical aspects of major processes, such as oxidation, diffusion, ion implantation, and epitaxy. Other topics covered include: high performance MOS and bipolar devices including ultra-thin gate oxides, implant-damage enhanced diffusion, advanced metrology, and new materials such as Silicon Germanium (SiGe). Includes audio/video content: AV lectures. This course is offered to graduates and focuses on understanding the fundamental principles of the "front-end" processes used in the fabrication of devices for silicon integrated circuits. This includes advanced physical models and practical aspects of major processes, such as oxidation, diffusion, ion implantation, and epitaxy. Other topics covered include: high performance MOS and bipolar devices including ultra-thin gate oxides, implant-damage enhanced diffusion, advanced metrology, and new materials such as Silicon Germanium (SiGe).

Subjects

fabrication processes | fabrication processes | silicon | silicon | integrated circuits | integrated circuits | monolithic integrated circuits | monolithic integrated circuits | physical models | physical models | bulk crystal growth | bulk crystal growth | thermal oxidation | thermal oxidation | solid-state diffusion | solid-state diffusion | ion implantation | ion implantation | epitaxial deposition | epitaxial deposition | chemical vapor deposition | chemical vapor deposition | physical vapor deposition | physical vapor deposition | refractory metal silicides | refractory metal silicides | plasma and reactive ion etching | plasma and reactive ion etching | rapid thermal processing | rapid thermal processing | process modeling | process modeling | process simulation | process simulation | technological limitations | technological limitations | integrated circuit design | integrated circuit design | integrated circuit fabrication | integrated circuit fabrication | device operation | device operation | sige materials | sige materials | processing | processing

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.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allavcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.895 Essential Coding Theory (MIT) 6.895 Essential Coding Theory (MIT)

Description

This course introduces the theory of error-correcting codes to computer scientists. This theory, dating back to the works of Shannon and Hamming from the late 40's, overflows with theorems, techniques, and notions of interest to theoretical computer scientists. The course will focus on results of asymptotic and algorithmic significance. Principal topics include: Construction and existence results for error-correcting codes. Limitations on the combinatorial performance of error-correcting codes. Decoding algorithms. Applications in computer science. This course introduces the theory of error-correcting codes to computer scientists. This theory, dating back to the works of Shannon and Hamming from the late 40's, overflows with theorems, techniques, and notions of interest to theoretical computer scientists. The course will focus on results of asymptotic and algorithmic significance. Principal topics include: Construction and existence results for error-correcting codes. Limitations on the combinatorial performance of error-correcting codes. Decoding algorithms. Applications in computer science.

Subjects

error-correcting codes | error-correcting codes | theoretical computer scientists | theoretical computer scientists | Shannon | Shannon | Hamming | Hamming | theorems | theorems | techniques | techniques | asymptotic | asymptotic | algorithmic significance | algorithmic significance | limitations | limitations | combinatorial performance | combinatorial performance | decoding algorithms | decoding algorithms | applications | applications | computer science | computer science

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.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-6.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.774 Physics of Microfabrication: Front End Processing (MIT)

Description

This course is offered to graduates and focuses on understanding the fundamental principles of the "front-end" processes used in the fabrication of devices for silicon integrated circuits. This includes advanced physical models and practical aspects of major processes, such as oxidation, diffusion, ion implantation, and epitaxy. Other topics covered include: high performance MOS and bipolar devices including ultra-thin gate oxides, implant-damage enhanced diffusion, advanced metrology, and new materials such as Silicon Germanium (SiGe).

Subjects

fabrication processes | silicon | integrated circuits | monolithic integrated circuits | physical models | bulk crystal growth | thermal oxidation | solid-state diffusion | ion implantation | epitaxial deposition | chemical vapor deposition | physical vapor deposition | refractory metal silicides | plasma and reactive ion etching | rapid thermal processing | process modeling | process simulation | technological limitations | integrated circuit design | integrated circuit fabrication | device operation | sige materials | processing

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allsimplifiedchinesecourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

Copyright for librarians

Description

Society and EIFL, a consortium of libraries from 50 countries in Africa, Asia and Europe. The goal of the project is to provide librarians in developing and transitional countries information concerning copyright law. More specifically, it aspires to inform librarians concerning: 1) copyright law in general 2) the aspects of copyright law that most affect libraries 3) how librarians in the future could most effectively participate in 4) the processes by which copyright law is interpreted and shaped.

Subjects

law | libraries | developing | transitional | public domain | basic | undergraduate | graduate-level | faculty | copyright | librarian | library | information | internet | society | eifl | africa | asia | europe | countries | berkman | international framework | international | framework | rights | exceptions | limitations | enforcement | activism | introduction | Law | M000

License

Attribution 2.0 UK: England & Wales Attribution 2.0 UK: England & Wales http://creativecommons.org/licenses/by/2.0/uk/ http://creativecommons.org/licenses/by/2.0/uk/

Site sourced from

http://dspace.jorum.ac.uk/oai/request?verb=ListRecords&metadataPrefix=oai_dc

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | decision | decision-making | reasoning | optimization | autonomous | autonomous systems | decision support | algorithms | artificial intelligence | a.i. | operations | operations research | logic | deduction | heuristic search | constraint-based search | model-based reasoning | planning | execution | uncertainty | machine learning | linear programming | dynamic programming | integer programming | network optimization | decision analysis | decision theoretic planning | Markov decision process | scheme | propositional logic | constraints | Markov processes | computational performance | satisfaction | learning algorithms | system state | state | search treees | plan spaces | model theory | decision trees | function approximators | optimization algorithms | limitations | tradeoffs | search and reasoning | game tree search | local stochastic search | stochastic | genetic algorithms | constraint satisfaction | propositional inference | rule-based systems | rule-based | model-based diagnosis | neural nets | reinforcement learning | web-based | search trees

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

24.119 Mind and Machines (MIT)

Description

This course is an introduction to many of the central issues in a branch of philosophy called philosophy of mind. Some of the questions we will discuss include the following. Can computers think? Is the mind an immaterial thing? Or is the mind the brain? Or does the mind stand to the brain as a computer program stands to the hardware? How can creatures like ourselves think thoughts that are "about" things? (For example, we can all think that Aristotle is a philosopher, and in that sense think "about" Aristotle, but what is the explanation of this quite remarkable ability?) Can I know whether your experiences and my experiences when we look at raspberries, fire trucks and stop lights are the same? Can consciousness be given a scientific explanation?

Subjects

artificial intelligence | psychology | philosophy | Turing Machines | consciousness | computer limitations | computation | neurophysiology | Turing test | the analog/digital distinction | Chinese Room argument | causal efficacy of content | inverted spectrum | mental representation | procedural semantics | connectionism

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | decision | decision-making | reasoning | optimization | autonomous | autonomous systems | decision support | algorithms | artificial intelligence | a.i. | operations | operations research | logic | deduction | heuristic search | constraint-based search | model-based reasoning | planning | execution | uncertainty | machine learning | linear programming | dynamic programming | integer programming | network optimization | decision analysis | decision theoretic planning | Markov decision process | scheme | propositional logic | constraints | Markov processes | computational performance | satisfaction | learning algorithms | system state | state | search treees | plan spaces | model theory | decision trees | function approximators | optimization algorithms | limitations | tradeoffs | search and reasoning | game tree search | local stochastic search | stochastic | genetic algorithms | constraint satisfaction | propositional inference | rule-based systems | rule-based | model-based diagnosis | neural nets | reinforcement learning | web-based | search trees

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

24.119 Mind and Machines (MIT)

Description

This course is an introduction to many of the central issues in the philosophy of mind, with an emphasis on consciousness and the mind-body problem.

Subjects

artificial intelligence | psychology | philosophy | turning machines | consciousness | computer limitations | computations | neurophysiology | Turing test | the analog/digital distinction | Chinese Room argument | causal efficacy of content | inverted spectrum | mental representation | procedural semantics | connectionism

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.774 Physics of Microfabrication: Front End Processing (MIT)

Description

This course is offered to graduates and focuses on understanding the fundamental principles of the "front-end" processes used in the fabrication of devices for silicon integrated circuits. This includes advanced physical models and practical aspects of major processes, such as oxidation, diffusion, ion implantation, and epitaxy. Other topics covered include: high performance MOS and bipolar devices including ultra-thin gate oxides, implant-damage enhanced diffusion, advanced metrology, and new materials such as Silicon Germanium (SiGe).

Subjects

fabrication processes | silicon | integrated circuits | monolithic integrated circuits | physical models | bulk crystal growth | thermal oxidation | solid-state diffusion | ion implantation | epitaxial deposition | chemical vapor deposition | physical vapor deposition | refractory metal silicides | plasma and reactive ion etching | rapid thermal processing | process modeling | process simulation | technological limitations | integrated circuit design | integrated circuit fabrication | device operation | sige materials | processing

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.895 Essential Coding Theory (MIT)

Description

This course introduces the theory of error-correcting codes to computer scientists. This theory, dating back to the works of Shannon and Hamming from the late 40's, overflows with theorems, techniques, and notions of interest to theoretical computer scientists. The course will focus on results of asymptotic and algorithmic significance. Principal topics include: Construction and existence results for error-correcting codes. Limitations on the combinatorial performance of error-correcting codes. Decoding algorithms. Applications in computer science.

Subjects

error-correcting codes | theoretical computer scientists | Shannon | Hamming | theorems | techniques | asymptotic | algorithmic significance | limitations | combinatorial performance | decoding algorithms | applications | computer science

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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata