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Description

6.777J / 2.372J is an introduction to microsystem design. Topics covered include: material properties, microfabrication technologies, structural behavior, sensing methods, fluid flow, microscale transport, noise, and amplifiers feedback systems. Student teams design microsystems (sensors, actuators, and sensing/control systems) of a variety of types, (e.g., optical MEMS, bioMEMS, inertial sensors) to meet a set of performance specifications (e.g., sensitivity, signal-to-noise) using a realistic microfabrication process. There is an emphasis on modeling and simulation in the design process. Prior fabrication experience is desirable. The course is worth 4 Engineering Design Points. 6.777J / 2.372J is an introduction to microsystem design. Topics covered include: material properties, microfabrication technologies, structural behavior, sensing methods, fluid flow, microscale transport, noise, and amplifiers feedback systems. Student teams design microsystems (sensors, actuators, and sensing/control systems) of a variety of types, (e.g., optical MEMS, bioMEMS, inertial sensors) to meet a set of performance specifications (e.g., sensitivity, signal-to-noise) using a realistic microfabrication process. There is an emphasis on modeling and simulation in the design process. Prior fabrication experience is desirable. The course is worth 4 Engineering Design Points.Subjects

microsystem design | microsystem design | material properties | material properties | microfabrication technologies | microfabrication technologies | structural behavior | structural behavior | sensing methods | sensing methods | fluid flow | fluid flow | microscale transport | microscale transport | noise | noise | amplifiers feedback systems | amplifiers feedback systems | sensors | sensors | actuators | actuators | sensing/control systems | sensing/control systems | optical MEMS | optical MEMS | bioMEMS | bioMEMS | inertial sensors | inertial sensors | sensitivity | sensitivity | signal-to-noise | signal-to-noise | realistic microfabrication process | realistic microfabrication processLicense

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See all metadata16.881 Robust System Design (MIT) 16.881 Robust System Design (MIT)

Description

This course was created for the "product development" track of MIT's System Design and Management Program (SDM) in conjunction with the Center for Innovation in Product Development. After taking this course, a student should be able to: Formulate measures of performance of a system or quality characteristics. These quality characteristics are to be made robust to noise affecting the system. Sythesize and select design concepts for robustness. Identify noise factors whose variation may affect the quality characteristics. Estimate the robustness of any given design (experimentally and analytically). Formulate and implement methods to reduce the effects of noise (parameter design, active control, adjustment). Select rational tolerances for a design. Explain the role of robust design This course was created for the "product development" track of MIT's System Design and Management Program (SDM) in conjunction with the Center for Innovation in Product Development. After taking this course, a student should be able to: Formulate measures of performance of a system or quality characteristics. These quality characteristics are to be made robust to noise affecting the system. Sythesize and select design concepts for robustness. Identify noise factors whose variation may affect the quality characteristics. Estimate the robustness of any given design (experimentally and analytically). Formulate and implement methods to reduce the effects of noise (parameter design, active control, adjustment). Select rational tolerances for a design. Explain the role of robust designSubjects

robust system design | robust system design | quality characteristics | quality characteristics | product development | product development | noise factors | noise factors | parameter design | parameter design | active control | active control | rational tolerances | rational tolerancesLicense

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Includes audio/video content: AV special element audio. This class explores sound and what can be done with it. Sources are recorded from students' surroundings - sampled and electronically generated (both analog and digital). Assignments include composing with the sampled sounds, feedback, and noise, using digital signal processing (DSP), convolution, algorithms, and simple mixing. The class focuses on sonic and compositional aspects rather than technology, math, or acoustics, though these are examined in varying detail. Students complete weekly composition and listening assignments; material for the latter is drawn from sound art, experimental electronica, conventional and non-conventional classical electronic works, popular music, and previous students' compositions. Includes audio/video content: AV special element audio. This class explores sound and what can be done with it. Sources are recorded from students' surroundings - sampled and electronically generated (both analog and digital). Assignments include composing with the sampled sounds, feedback, and noise, using digital signal processing (DSP), convolution, algorithms, and simple mixing. The class focuses on sonic and compositional aspects rather than technology, math, or acoustics, though these are examined in varying detail. Students complete weekly composition and listening assignments; material for the latter is drawn from sound art, experimental electronica, conventional and non-conventional classical electronic works, popular music, and previous students' compositions.Subjects

computer music | computer music | sound | sound | music | music | audio | audio | listening | listening | electronic music | electronic music | new music | new music | electronica | electronica | sound art | sound art | noise | noise | noise music | noise music | avant-garde | avant-garde | contemporary music | contemporary music | modern music | modern music | composition | composition | recording | recording | music production | music production | recording studio | recording studio | audio software | audio software | recording software | recording software | sampling | sampling | synthesis | synthesis | audio engineering | audio engineering | mixing | mixing | Radiohead | RadioheadLicense

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This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation. This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation.Subjects

system identification; estimation; least squares estimation; Kalman filter; noise dynamics; system representation; function approximation theory; neural nets; radial basis functions; wavelets; volterra expansions; informative data sets; persistent excitation; asymptotic variance; central limit theorem; model structure selection; system order estimate; maximum likelihood; unbiased estimates; Cramer-Rao lower bound; Kullback-Leibler information distance; Akaike?s information criterion; experiment design; model validation. | system identification; estimation; least squares estimation; Kalman filter; noise dynamics; system representation; function approximation theory; neural nets; radial basis functions; wavelets; volterra expansions; informative data sets; persistent excitation; asymptotic variance; central limit theorem; model structure selection; system order estimate; maximum likelihood; unbiased estimates; Cramer-Rao lower bound; Kullback-Leibler information distance; Akaike?s information criterion; experiment design; model validation. | system identification | system identification | estimation | estimation | least squares estimation | least squares estimation | Kalman filter | Kalman filter | noise dynamics | noise dynamics | system representation | system representation | function approximation theory | function approximation theory | neural nets | neural nets | radial basis functions | radial basis functions | wavelets | wavelets | volterra expansions | volterra expansions | informative data sets | informative data sets | persistent excitation | persistent excitation | asymptotic variance | asymptotic variance | central limit theorem | central limit theorem | model structure selection | model structure selection | system order estimate | system order estimate | maximum likelihood | maximum likelihood | unbiased estimates | unbiased estimates | Cramer-Rao lower bound | Cramer-Rao lower bound | Kullback-Leibler information distance | Kullback-Leibler information distance | Akaike?s information criterion | Akaike?s information criterion | experiment design | experiment design | model validation | model validationLicense

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 metadataMini Project Communication Link Simulation Channels And Noise Lecture

Description

The objective of this module is to have built communication links using existing AM modulation, PSK modulation and demodulation blocks, constructed AM modulators and constructed PSK modulators using operational function blocks based on their mathematical expressions, and conducted simulations of the links and modulators, all in Simulink®.Subjects

2ele0064 | additive white gaussian noise | channel | communication link simulation | communication systems | communications | demodulation | digital modulation | electronics | engineering | engsc | engscoer | errors performance degradation | expressions | fading and delay of channels | johnson noise | links | mathematical expressions | matlab | measures of system performance | mini project | modulation | noise | operational function blocks | school of electronic communications and electrical | sources of noise | system performance | thermal noise | ukoer | uniofhertsoer | university of hertfordshire | Engineering | H000License

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See all metadata6.441 Transmission of Information (MIT) 6.441 Transmission of Information (MIT)

Description

6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include: mathematical definition and properties of information; source coding theorem, lossless compression of data, optimal lossless coding; noisy communication channels, channel coding theorem, the source-channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels. 6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include: mathematical definition and properties of information; source coding theorem, lossless compression of data, optimal lossless coding; noisy communication channels, channel coding theorem, the source-channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels.Subjects

transmission of information | transmission of information | quantitative theory of information | quantitative theory of information | efficient communication systems | efficient communication systems | mathematical definition of information | mathematical definition of information | properties of information | properties of information | source coding theorem | source coding theorem | lossless compression of data | lossless compression of data | optimal lossless coding | optimal lossless coding | noisy communication channels | noisy communication channels | channel coding theorem | channel coding theorem | the source-channel separation theorem | the source-channel separation theorem | multiple access channels | multiple access channels | broadcast channels | broadcast channels | gaussian noise | gaussian noise | time-varying channels | time-varying channels | lossless data compression | lossless data compression | telecommunications | telecommunications | data transmission | data transmissionLicense

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See all metadataII "Junior Lab" (MIT) II "Junior Lab" (MIT)

Description

Junior Lab consists of two undergraduate courses in experimental physics. The courses are offered by the MIT Physics Department, and are usually taken by Juniors (hence the name). Officially, the courses are called Experimental Physics I and II and are numbered 8.13 for the first half, given in the fall semester, and 8.14 for the second half, given in the spring.The purposes of Junior Lab are to give students hands-on experience with some of the experimental basis of modern physics and, in the process, to deepen their understanding of the relations between experiment and theory, mostly in atomic and nuclear physics. Each term, students choose 5 different experiments from a list of 21 total labs. Junior Lab consists of two undergraduate courses in experimental physics. The courses are offered by the MIT Physics Department, and are usually taken by Juniors (hence the name). Officially, the courses are called Experimental Physics I and II and are numbered 8.13 for the first half, given in the fall semester, and 8.14 for the second half, given in the spring.The purposes of Junior Lab are to give students hands-on experience with some of the experimental basis of modern physics and, in the process, to deepen their understanding of the relations between experiment and theory, mostly in atomic and nuclear physics. Each term, students choose 5 different experiments from a list of 21 total labs.Subjects

Junior Lab | Junior Lab | experimental | experimental | atomic | atomic | nuclear | nuclear | physics | physics | optics | optics | photoelectric effect | photoelectric effect | poisson | poisson | statistics | statistics | electromagnetic pulse | electromagnetic pulse | compton scattering | compton scattering | Franck-Hertz experiment | Franck-Hertz experiment | relativistic dynamics | relativistic dynamics | nuclear magnetic resonance | nuclear magnetic resonance | spin echoes | spin echoes | cosmic-ray muons | cosmic-ray muons | Rutherford Scattering | Rutherford Scattering | emission spectra | emission spectra | neutron physics | neutron physics | Johnson noise | Johnson noise | shot noise | shot noise | quantum mechanics | quantum mechanics | alpha decay | alpha decay | radio astrophysics | radio astrophysics | Zeeman effect | Zeeman effect | rubidium | rubidium | M?ssbauer | M?ssbauer | spectroscopy | spectroscopy | X-Ray physics | X-Ray physics | superconductivity | superconductivity | Doppler-free | Doppler-free | laser | laserLicense

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See all metadata6.050J Information and Entropy (MIT) 6.050J Information and Entropy (MIT)

Description

6.050J / 2.110J presents the unified theory of information with applications to computing, communications, thermodynamics, and other sciences. It covers digital signals and streams, codes, compression, noise, and probability, reversible and irreversible operations, information in biological systems, channel capacity, maximum-entropy formalism, thermodynamic equilibrium, temperature, the Second Law of Thermodynamics, and quantum computation. Designed for MIT freshmen as an elective, this course has been jointly developed by MIT's Departments of Electrical Engineering and Computer Science and Mechanical Engineering. There is no known course similar to 6.050J / 2.110J offered at any other university.  6.050J / 2.110J presents the unified theory of information with applications to computing, communications, thermodynamics, and other sciences. It covers digital signals and streams, codes, compression, noise, and probability, reversible and irreversible operations, information in biological systems, channel capacity, maximum-entropy formalism, thermodynamic equilibrium, temperature, the Second Law of Thermodynamics, and quantum computation. Designed for MIT freshmen as an elective, this course has been jointly developed by MIT's Departments of Electrical Engineering and Computer Science and Mechanical Engineering. There is no known course similar to 6.050J / 2.110J offered at any other university. Subjects

information and entropy | information and entropy | computing | computing | communications | communications | thermodynamics | thermodynamics | digital signals and streams | digital signals and streams | codes | codes | compression | compression | noise | noise | probability | probability | reversible operations | reversible operations | irreversible operations | irreversible operations | information in biological systems | information in biological systems | channel capacity | channel capacity | aximum-entropy formalism | aximum-entropy formalism | thermodynamic equilibrium | thermodynamic equilibrium | temperature | temperature | second law of thermodynamics quantum computation | second law of thermodynamics quantum computation | maximum-entropy formalism | maximum-entropy formalism | second law of thermodynamics | second law of thermodynamics | quantum computation | quantum computation | biological systems | biological systems | unified theory of information | unified theory of information | digital signals | digital signals | digital streams | digital streams | bits | bits | errors | errors | processes | processes | inference | inference | maximum entropy | maximum entropy | physical systems | physical systems | energy | energy | quantum information | quantum information | 6.050 | 6.050 | 2.110 | 2.110License

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This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm.More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithms This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm.More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithmsSubjects

coding techniques | coding techniques | the Shannon limit of additive white Gaussian noise channels | the Shannon limit of additive white Gaussian noise channels | performance analysis | performance analysis | Small signal constellations | Small signal constellations | coding gain | coding gain | Hard-decision and soft-decision decoding | Hard-decision and soft-decision decoding | Introduction to binary linear block codes | Introduction to binary linear block codes | Reed-Muller codes | Reed-Muller codes | finite fields | finite fields | Reed-Solomon and BCH codes | Reed-Solomon and BCH codes | binary linear convolutional codes | binary linear convolutional codes | Viterbi and BCJR algorithms | Viterbi and BCJR algorithms | Trellis representations of binary linear block codes | Trellis representations of binary linear block codes | trellis-based ML decoding | trellis-based ML decoding | Codes on graphs | Codes on graphs | sum-product | sum-product | max-product | max-product | decoding algorithms | decoding algorithms | Turbo codes | Turbo codes | LDPC codes and RA codes | LDPC codes and RA codes | Coding for the bandwidth-limited regime | Coding for the bandwidth-limited regime | Lattice codes | Lattice codes | Trellis-coded modulation | Trellis-coded modulation | Multilevel coding | Multilevel coding | Shaping | ShapingLicense

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See all metadata13.853 Computational Ocean Acoustics (MIT) 13.853 Computational Ocean Acoustics (MIT)

Description

This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research. This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research.Subjects

Wave equations | Wave equations | fluid and visco-elastic media | fluid and visco-elastic media | Wave-theory formulations | Wave-theory formulations | acoustic source radiation | acoustic source radiation | seismo-acoustic propagation | seismo-acoustic propagation | stratified ocean waveguides | stratified ocean waveguides | Wavenumber Integration | Wavenumber Integration | Normal Mode | Normal Mode | propagation in plane-stratified media | propagation in plane-stratified media | Seismo-Acoustic modeling | Seismo-Acoustic modeling | Seismic interface | Seismic interface | surface waves | surface waves | stratified seabed | stratified seabed | Parabolic Equation | Parabolic Equation | Coupled Mode | Coupled Mode | range-dependent ocean waveguides | range-dependent ocean waveguides | Numerical modeling | Numerical modeling | target scattering | target scattering | reverberation clutter | reverberation clutter | Ocean ambient noise modeling | Ocean ambient noise modeling | Fluid media | Fluid media | visco-elastic media | visco-elastic media | plane-stratified media | plane-stratified media | ice covers | ice covers | 2.068 | 2.068License

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See all metadata6.050J Information and Entropy (MIT) 6.050J Information and Entropy (MIT)

Description

Includes audio/video content: AV selected lectures. This course explores the ultimate limits to communication and computation, with an emphasis on the physical nature of information and information processing. Topics include: information and computation, digital signals, codes and compression, applications such as biological representations of information, logic circuits, computer architectures, and algorithmic information, noise, probability, error correction, reversible and irreversible operations, physics of computation, and quantum computation. The concept of entropy applied to channel capacity and to the second law of thermodynamics. Includes audio/video content: AV selected lectures. This course explores the ultimate limits to communication and computation, with an emphasis on the physical nature of information and information processing. Topics include: information and computation, digital signals, codes and compression, applications such as biological representations of information, logic circuits, computer architectures, and algorithmic information, noise, probability, error correction, reversible and irreversible operations, physics of computation, and quantum computation. The concept of entropy applied to channel capacity and to the second law of thermodynamics.Subjects

information and entropy | information and entropy | computing | computing | communications | communications | thermodynamics | thermodynamics | digital signals and streams | digital signals and streams | codes | codes | compression | compression | noise | noise | probability | probability | reversible operations | reversible operations | irreversible operations | irreversible operations | information in biological systems | information in biological systems | channel capacity | channel capacity | maximum-entropy formalism | maximum-entropy formalism | thermodynamic equilibrium | thermodynamic equilibrium | temperature | temperature | second law of thermodynamics quantum computation | second law of thermodynamics quantum computationLicense

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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Includes audio/video content: AV special element video. This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data. Enrollment preference is given to juniors and seniors. Includes audio/video content: AV special element video. This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data. Enrollment preference is given to juniors and seniors.Subjects

DNA analysis | DNA analysis | Fourier analysis | Fourier analysis | FFT | FFT | DNA melting | DNA melting | electronics | electronics | microscopy | microscopy | microscope | microscope | probes | probes | biology | biology | atomic force microscope | atomic force microscope | AFM | AFM | scanning probe microscope | scanning probe microscope | image processing | image processing | MATLAB | MATLAB | convolution | convolution | optoelectronics | optoelectronics | rheology | rheology | fluorescence | fluorescence | noise | noise | detector | detector | optics | optics | diffraction | diffraction | optical trap | optical trap | 3D | 3D | 3-D | 3-D | three-dimensional imaging | three-dimensional imaging | visualization | visualizationLicense

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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Includes audio/video content: AV lectures. This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm. More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and Includes audio/video content: AV lectures. This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm. More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product andSubjects

coding techniques | coding techniques | the Shannon limit of additive white Gaussian noise channels | the Shannon limit of additive white Gaussian noise channels | performance analysis | performance analysis | Small signal constellations | Small signal constellations | coding gain | coding gain | Hard-decision and soft-decision decoding | Hard-decision and soft-decision decoding | Introduction to binary linear block codes | Introduction to binary linear block codes | Reed-Muller codes | Reed-Muller codes | finite fields | finite fields | Reed-Solomon and BCH codes | Reed-Solomon and BCH codes | binary linear convolutional codes | binary linear convolutional codes | Viterbi and BCJR algorithms | Viterbi and BCJR algorithms | Trellis representations of binary linear block codes | Trellis representations of binary linear block codes | trellis-based ML decoding | trellis-based ML decoding | Codes on graphs | Codes on graphs | sum-product | sum-product | max-product | max-product | decoding algorithms | decoding algorithms | Turbo codes | Turbo codes | LDPC codes and RA codes | LDPC codes and RA codes | Coding for the bandwidth-limited regime | Coding for the bandwidth-limited regime | Lattice codes. | Lattice codes. | Trellis-coded modulation | Trellis-coded modulation | Multilevel coding | Multilevel coding | Shaping | Shaping | Lattice codes | Lattice codesLicense

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This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. The course covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. Laboratory projects emphasize practical digital servo interfacing and implementation problems with timing, noise, and nonlinear devices. This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. The course covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. Laboratory projects emphasize practical digital servo interfacing and implementation problems with timing, noise, and nonlinear devices.Subjects

digital computer | digital computer | computation | computation | real-time computer | real-time computer | input-output | input-output | I/O | I/O | interface | interface | data converter | data converter | A/D converter | A/D converter | sampling | sampling | state-space | state-space | algorithm | algorithm | quantization | quantization | servo | servo | timing | timing | noise | noise | nonlinear | nonlinear | nonlinearity | nonlinearity | non-linear | non-linearLicense

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This course introduces theoretical and practical principles of design of oceanographic sensor systems. Topics include: transducer characteristics for acoustic, current, temperature, pressure, electric, magnetic, gravity, salinity, velocity, heat flow, and optical devices; limitations on these devices imposed by ocean environments; signal conditioning and recording; noise, sensitivity, and sampling limitations; and standards. Lectures by experts cover the principles of state-of-the-art systems being used in physical oceanography, geophysics, submersibles, acoustics. For lab work, day cruises in local waters allow students to prepare, deploy and analyze observations from standard oceanographic instruments. This course introduces theoretical and practical principles of design of oceanographic sensor systems. Topics include: transducer characteristics for acoustic, current, temperature, pressure, electric, magnetic, gravity, salinity, velocity, heat flow, and optical devices; limitations on these devices imposed by ocean environments; signal conditioning and recording; noise, sensitivity, and sampling limitations; and standards. Lectures by experts cover the principles of state-of-the-art systems being used in physical oceanography, geophysics, submersibles, acoustics. For lab work, day cruises in local waters allow students to prepare, deploy and analyze observations from standard oceanographic instruments.Subjects

Oceanography | Oceanography | monitoring | monitoring | instrumentation | instrumentation | experiment | experiment | sampling | sampling | transducer | transducer | meteorology | meteorology | calibration | calibration | noise | noise | ocean | ocean | water | water | sea water | sea water | telemetry | telemetry | data recorder | data recorder | satellite | satellite | current | current | salinity | salinity | pressure | pressure | corrosion | corrosion | underwater | underwaterLicense

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This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research. This course was originally offered in Course 13 ( This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research. This course was originally offered in Course 13 (Subjects

Wave equations | Wave equations | fluid and visco-elastic media | fluid and visco-elastic media | Wave-theory formulations | Wave-theory formulations | acoustic source radiation | acoustic source radiation | seismo-acoustic propagation | seismo-acoustic propagation | stratified ocean waveguides | stratified ocean waveguides | Wavenumber Integration | Wavenumber Integration | Normal Mode | Normal Mode | propagation in plane-stratified media | propagation in plane-stratified media | Seismo-Acoustic modeling | Seismo-Acoustic modeling | Seismic interface | Seismic interface | surface waves | surface waves | stratified seabed | stratified seabed | Parabolic Equation | Parabolic Equation | Coupled Mode | Coupled Mode | range-dependent ocean waveguides | range-dependent ocean waveguides | Numerical modeling | Numerical modeling | target scattering | target scattering | reverberation clutter | reverberation clutter | Ocean ambient noise modeling | Ocean ambient noise modeling | Fluid media | Fluid media | visco-elastic media | visco-elastic media | plane-stratified media | plane-stratified media | ice covers | ice coversLicense

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See all metadata6.441 Information Theory (MIT) 6.441 Information Theory (MIT)

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6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include mathematical definition and properties of information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels. 6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include mathematical definition and properties of information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels.Subjects

properties of information | properties of information | source coding theorem | source coding theorem | lossless compression | lossless compression | noisy communication | noisy communication | channel coding theorem | channel coding theorem | source channel separation theorem | source channel separation theorem | multiple access channels | multiple access channels | broadcast channels | broadcast channels | Gaussian noise | Gaussian noise | time-varying channels | time-varying channelsLicense

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See all metadata6.435 System Identification (MIT) 6.435 System Identification (MIT)

Description

This course is offered to graduates and includes topics such as mathematical models of systems from observations of their behavior; time series, state-space, and input-output models; model structures, parametrization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues. This course is offered to graduates and includes topics such as mathematical models of systems from observations of their behavior; time series, state-space, and input-output models; model structures, parametrization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues.Subjects

mathematical models | mathematical models | time series | time series | state-space | state-space | input-output models | input-output models | model structures | model structures | parametrization | parametrization | identifiability | identifiability | non-parametric methods | non-parametric methods | prediction error | prediction error | parameter estimation | parameter estimation | convergence | convergence | consistency | consistency | andasymptotic distribution | andasymptotic distribution | maximum likelihood estimation | maximum likelihood estimation | recursive estimation | recursive estimation | Kalman filters | Kalman filters | structure determination | structure determination | order estimation | order estimation | Akaike criterion | Akaike criterion | bounded noise models | bounded noise models | robustness | robustnessLicense

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See all metadata6.776 High Speed Communication Circuits (MIT) 6.776 High Speed Communication Circuits (MIT)

Description

6.776 covers circuit level design issues of high speed communication systems, with primary focus being placed on wireless and broadband data link applications. Specific circuit topics include transmission lines, high speed and low noise amplifiers, VCO's, mixers, power amps, high speed digital circuits, and frequency synthesizers. In addition to learning analysis skills for the above items, students will gain a significant amount of experience in simulating RF circuits in SPICE and also building RF circuits within a lab project. 6.776 covers circuit level design issues of high speed communication systems, with primary focus being placed on wireless and broadband data link applications. Specific circuit topics include transmission lines, high speed and low noise amplifiers, VCO's, mixers, power amps, high speed digital circuits, and frequency synthesizers. In addition to learning analysis skills for the above items, students will gain a significant amount of experience in simulating RF circuits in SPICE and also building RF circuits within a lab project.Subjects

integrated circuit design | integrated circuit design | communication systems | communication systems | wireless | wireless | broadband | broadband | data links | data links | circuit blocks | circuit blocks | communication transceivers | communication transceivers | phase-locked loops | phase-locked loops | PLL | PLL | narrowband | narrowband | low-noise | low-noise | amplifiers | amplifiers | mixers | mixers | voltage-controlled oscillators | voltage-controlled oscillators | power amplifiers | power amplifiers | high speed frequency dividers | high speed frequency dividers | passive component design | passive component design | on-chip inductors | on-chip inductors | capacitors | capacitors | transmission line modeling | transmission line modeling | S-parameters | S-parameters | Smith Chart | Smith ChartLicense

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6.977 focuses on the physics of the interaction of photons with semiconductor materials. The band theory of solids is used to calculate the absorption and gain of semiconductor media. The rate equation formalism is used to develop the concepts of laser threshold, population inversion and modulation response. Matrix methods and coupled mode theory are applied to resonator structures such as distributed feedback lasers, tunable lasers and microring devices. The course is also intended to introduce students to noise models for semiconductor devices and to applications of optoelectronic devices to fiber optic communications. This course is worth 12 Engineering Design points. 6.977 focuses on the physics of the interaction of photons with semiconductor materials. The band theory of solids is used to calculate the absorption and gain of semiconductor media. The rate equation formalism is used to develop the concepts of laser threshold, population inversion and modulation response. Matrix methods and coupled mode theory are applied to resonator structures such as distributed feedback lasers, tunable lasers and microring devices. The course is also intended to introduce students to noise models for semiconductor devices and to applications of optoelectronic devices to fiber optic communications. This course is worth 12 Engineering Design points.Subjects

semiconductor optoelectronics | semiconductor optoelectronics | photons | photons | semiconductor | semiconductor | band theory of solids | band theory of solids | rate equation formalism | rate equation formalism | laser threshold | laser threshold | population inversion | population inversion | modulation response | modulation response | Matrix methods | Matrix methods | coupled mode theory | coupled mode theory | resonator structures | resonator structures | distributed feedback lasers | distributed feedback lasers | tunable lasers | tunable lasers | microring devices | microring devices | noise models | noise models | optoelectronics | optoelectronics | fiber optic communications | fiber optic communicationsLicense

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See all metadataII "Junior Lab" (MIT) II "Junior Lab" (MIT)

Description

Junior Lab consists of two undergraduate courses in experimental physics. The courses are offered by the MIT Physics Department, and are usually taken by Juniors (hence the name). Officially, the courses are called Experimental Physics I and II and are numbered 8.13 for the first half, given in the fall semester, and 8.14 for the second half, given in the spring. The purposes of Junior Lab are to give students hands-on experience with some of the experimental basis of modern physics and, in the process, to deepen their understanding of the relations between experiment and theory, mostly in atomic and nuclear physics. Each term, students choose 5 different experiments from a list of 21 total labs. Junior Lab consists of two undergraduate courses in experimental physics. The courses are offered by the MIT Physics Department, and are usually taken by Juniors (hence the name). Officially, the courses are called Experimental Physics I and II and are numbered 8.13 for the first half, given in the fall semester, and 8.14 for the second half, given in the spring. The purposes of Junior Lab are to give students hands-on experience with some of the experimental basis of modern physics and, in the process, to deepen their understanding of the relations between experiment and theory, mostly in atomic and nuclear physics. Each term, students choose 5 different experiments from a list of 21 total labs.Subjects

Junior Lab | Junior Lab | experimental | experimental | atomic | atomic | nuclear | nuclear | physics | physics | optics | optics | photoelectric effect | photoelectric effect | poisson | poisson | statistics | statistics | electromagnetic pulse | electromagnetic pulse | compton scattering | compton scattering | Franck-Hertz experiment | Franck-Hertz experiment | relativistic dynamics | relativistic dynamics | nuclear magnetic resonance | nuclear magnetic resonance | spin echoes | spin echoes | cosmic-ray muons | cosmic-ray muons | Rutherford Scattering | Rutherford Scattering | emission spectra | emission spectra | neutron physics | neutron physics | Johnson noise | Johnson noise | shot noise | shot noise | quantum mechanics | quantum mechanics | alpha decay | alpha decay | radio astrophysics | radio astrophysics | Zeeman effect | Zeeman effect | rubidium | rubidium | M?ssbauer | M?ssbauer | spectroscopy | spectroscopy | X-Ray physics | X-Ray physics | superconductivity | superconductivity | Doppler-free | Doppler-free | laser | laserLicense

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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

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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

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See all metadata8.044 Statistical Physics I (MIT) 8.044 Statistical Physics I (MIT)

Description

This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.This course is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges. This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.This course is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges.Subjects

probability | probability | statistical mechanics | statistical mechanics | thermodynamics | thermodynamics | random variables | random variables | joint and conditional probability densities | joint and conditional probability densities | functions of a random variable | functions of a random variable | macroscopic variables | macroscopic variables | thermodynamic equilibrium | thermodynamic equilibrium | fundamental assumption of statistical mechanics | fundamental assumption of statistical mechanics | microcanonical and canonical ensembles | microcanonical and canonical ensembles | First | second | and third laws of thermodynamics | First | second | and third laws of thermodynamics | magnetism | magnetism | polyatomic gases | polyatomic gases | thermal radiation | thermal radiation | electrons in solids | electrons in solids | noise in electronic devices | noise in electronic devicesLicense

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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

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