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For more details on NPTEL visit Course Description : Introduction to Information Theory and Coding - Definition of Information Measure and Entropy - Extension of An Information Source and Markov Source - Adjoint of An Information Source, Joint and Conditional Information Measures - Properties of Joint and Conditional Information Measures and a Markov Source - Asymptotic Properties of Entropy and Problem Solving in Entropy - Block Code and Its Properties - Instantaneous Code and Its Properties - Kraft-Mcmillan Equality and Compact Codes - Shannon's First Theorem - Coding Strategies and Introduction to Huffman Coding - Huffman Coding and Proof of Its Optimality - Competitive Optimality of The Shannon Code - Non-Binary Huffman Code and Other Codes - Adaptive Huffman Coding - Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding Introduction to Information Channel - Equivocation and Mutual Information - Properties of Different Information Channels - Reduction of Information Channels - Properties of Mutual Information and Introduction to Channel Capacity - Calculation of Channel Capacity for Different Information Channel - Shannon's Second Theorem - Discussion on Error Free Communication Over Noisy Channel - Error Free Communication Over a Binary Symmetric Channel - Differential Entropy and Evaluation of Mutual Information - Channel Capacity of a Bandlimited Continuous Channel - Introduction to Rate-Distortion Theory - Definition and Properties of Rate-Distortion Functions - Calculation of Rate-Distortion Functions - Computational Approach For Calculation of Rate-Distortion Functions - Introduction to Quantization - Lloyd-Max Quantizer - Companded Quantization - Variable Length Coding and Problem Solving In Quantizer Design - Vector Quantization - Transform - Transform Coding Other Resources Syllabus Citation The above video lectures are presented by IITBombay, India, under the program NPTEL, there are more than 350 NPTEL courses Online available. Carrier ModulationBinary Phase Shift Keying (BPSK) ModulationPDF0.133 kb. Channel CodingTurbo CodesPDF0.071 kb. Carrier ModulationMinimum Shift Keying (MSK) ModulationPDF0.135 kb. Quantization and CodingPulse Code Modulation (PCM)PDF0.134 kb. Random ProcessesStochastic ProcessesPDF0.08 kb. Lectures 1.Introduction to Information Theory and Coding 2.Definition of Information Measure and Entropy 3.Extension of An Information Source and Markov Source 4.Adjoint of An Information Source, Joint and Conditional Information Measures 5.Properties of Joint and Conditional Information Measures and a Markov Source 6.Asymptotic Properties of Entropy and Problem Solving in Entropy 7.Block Code and Its Properties 8.Instantaneous Code and Its Properties 9.Kraft-Mcmillan Equality and Compact Codes 10.Shannons First Theorem 11.Coding Strategies and Introduction to Huffman Coding 12.Huffman Coding and Proof of Its Optimality 13.Competitive Optimality of The Shannon Code 14.Non-Binary Huffman Code and Other Codes 15.Adaptive Huffman Coding part-1 16.Adaptive Huffman Coding Part-2 17.Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding 18.Arithmetic Coding Part-1 19.Arithmetic Coding Part-2 20.Introduction to Information Channel 21.Equivocation and Mutual Information 22.Properties of Different Information Channels 23.Reduction of Information Channels 24.Properties of Mutual Information and Introduction to Channel Capacity 25.Calculation of Channel Capacity for Different Information Channel 26.Shannons Second Theorem 27.Discussion on Error Free Communication Over Noisy Channel 28.Error Free Communication Over a Binary Symmetric Channel 29.Differential Entropy and Evaluation of Mutual Information 30.Channel Capacity of a Bandlimited Continuous Channel 31.Introduction to Rate-Distortion Theory 32.Definition and Properties of Rate-Distortion Functions 33.Calculation of Rate-Distortion Functions 34.Computational Approach For Calculation of Rate-Distortion Functions 35.Introduction to Quantization 36.Lloyd-Max Quantizer 37.Companded Quantization 38.Variable Length Coding and Problem Solving In Quantizer Design 39.Vector Quantization 40.Transform Part-1 41.Transform Coding Part-2 1.Introduction to Information Theory and Coding 2.Definition of Information Measure and Entropy 3.Extension of An Information Source and Markov Source 4.Adjoint of An Information Source, Joint and Conditional Information Measures 5.Properties of Joint and Conditional Information Measures and a Markov Source 6.Asymptotic Properties of Entropy and Problem Solving in Entropy 7.Block Code and Its Properties 8.Instantaneous Code and Its Properties 9.Kraft-Mcmillan Equality and Compact Codes 10.Shannons First Theorem 11.Coding Strategies and Introduction to Huffman Coding 12.Huffman Coding and Proof of Its Optimality 13.Competitive Optimality of The Shannon Code 14.Non-Binary Huffman Code and Other Codes 15.Adaptive Huffman Coding part-1 16.Adaptive Huffman Coding Part-2 17.Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding 18.Arithmetic Coding Part-1 19.Arithmetic Coding Part-2 20.Introduction to Information Channel 21.Equivocation and Mutual Information 22.Properties of Different Information Channels 23.Reduction of Information Channels 24.Properties of Mutual Information and Introduction to Channel Capacity 25.Calculation of Channel Capacity for Different Information Channel 26.Shannons Second Theorem 27.Discussion on Error Free Communication Over Noisy Channel 28.Error Free Communication Over a Binary Symmetric Channel 29.Differential Entropy and Evaluation of Mutual Information 30.Channel Capacity of a Bandlimited Continuous Channel 31.Introduction to Rate-Distortion Theory 32.Definition and Properties of Rate-Distortion Functions 33.Calculation of Rate-Distortion Functions 34.Computational Approach For Calculation of Rate-Distortion Functions 35.Introduction to Quantization 36.Lloyd-Max Quantizer 37.Companded Quantization 38.Variable Length Coding and Problem Solving In Quantizer Design 39.Vector Quantization 40.Transform Part-1 41.Transform Coding Part-2 Lecture 1: Introduction to Information Theory and Coding 1 2 3 4 5 Download: MP4,FLV & 3GP 17278 views Lecture Details : Information Theory and Coding by Prof. Random ProcessesSome useful DistributionsPDF0.134 kb. Carrier ModulationQuaternary Phase Shift Keying QPSK) and M-ary PSK ModulationsPDF0.233 kb.
Carrier ModulationTiming SynchronizationPDF0.203 kb. Signal Representation and Baseband ProcessingOrthogonalityPDF0.151 kb. Channel CodingBlock CodesPDF0.193 kb. About Blog Terms Privacy Contact FreeVideoLectures.com is not sponsered or endorsed or affiliated to/by any University/College/School 2016 FreeVideoLectures.com All Rights Reserved. Quantization and CodingDifferential Pulse Code Modulation (DPCM)PDF0.128 kb. Signal Representation and Baseband ProcessingResponse of Linear System to Random ProcessesPDF0.161 kb. Channel CodingIntroduction to Error Control CodingPDF0.089 kb. Introduction to Digital Communications and Information TheoryInformation Theoretic Approach to Digital CommunicationsPDF0.198 kb.
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