Chapter 5：Differential Entropy and Gaussian Channels, 5.6 Capacity of correlated parallel Gaussian channels, 5.7 Non-Gaussian discrete-time memoryless channels, 5.8 Capacity of band-limited white Gaussian channel

Homepage » ALL COURSE » College of Electrical and Computer Engineering » Information Theory – 107 Academic Year | College of Electrical and Computer Engineering Prof. Po-Ning Chen » Chapter 5：Differential Entropy and Gaussian Channels, 5.6 Capacity of correlated parallel Gaussian channels, 5.7 Non-Gaussian discrete-time memoryless channels, 5.8 Capacity of band-limited white Gaussian channel

Chapter 5：Differential Entropy and Gaussian Channels, 5.6 Capacity of correlated parallel Gaussian channels, 5.7 Non-Gaussian discrete-time memoryless channels, 5.8 Capacity of band-limited white Gaussian channel

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Course Content	Course Video	Course Download
Overview: The philosophy behind information theory	Watch Online	MP4 Download
Chapter 1:Introduction	Watch Online	MP4 Download
Appendix A:Overview on Suprema and Limits A.1 Supremum and maximum A.2 Infimum and minimum A.3 Boundedness and suprema operations A.4 Sequences and their limits	Watch Online	MP4 Download
Appendix A:Overview on Suprema and Limits Review A.1-A.4 A.5 Equivalence	Watch Online	MP4 Download
Appendix B:Overview in Probability and Random Processes B.1 Probability space B.2 Random variables and random processes	Watch Online	MP4 Download
Appendix B:Overview in Probability and Random Processes B.3 Statistical properties of random sources	Watch Online	MP4 Download
Appendix B:Overview in Probability and Random Processes B.5 Ergodicity and law of large numbers B.6 Central limit theorem B.7 Convexity, concavity and Jensen’s inequality B.8 Lagrange multipliers tech. & KKT conditions	Watch Online	MP4 Download
Chapter 2：Information Measures for Discrete Systems 2.1.1 Self-information 2.1.2 Entropy 2.1.3 Properties of entropy 2.1.4 Joint entropy and conditional entropy 2.1.5 Properties of joint and conditional entropy 2.2 Mutual information 2.2.1 Properties of m	Watch Online	MP4 Download
Chapter 2：Information Measures for Discrete Systems 2.4 Data processing inequality 2.5 Fano’s inequality	Watch Online	MP4 Download
Chapter 2：Information Measures for Discrete Systems 2.6 Divergence and variational distance	Watch Online	MP4 Download
Chapter 2：Information Measures for Discrete System 2.7 Convexity/concavity of information measures 2.8 Fundamentals of hypothesis testing 2.9 R´enyi’s information measures	Watch Online	MP4 Download
Chapter 3：Lossless Data Compression 3.1 Principles of data compression 3.2.1 Block codes for DMS 3.2.2 Block Codes for Stationary Ergodic Sources	Watch Online	MP4 Download
Chapter 3：Lossless Data Compression 3.3 Variable-Length Code for Lossless Data Comp. 3.3.1 Non-singular Codes and Uniquely Decodable Codes 3.3.2 Prefix or Instantaneous Codes	Watch Online	MP4 Download
Chapter 3：Lossless Data Compression 3.3.3 Examples of Binary Prefix Codes	Watch Online	MP4 Download
Chapter 3：Lossless Data Compression 3.3.4 Universal Lossless Variable-Length Codes	Watch Online	MP4 Download
Chapter 4:Data Transmission and Channel Capacity 4.3 Block codes for data transmission over DMCs(1/3)	Watch Online	MP4 Download
Chapter 4:Data Transmission and Channel Capacity 4.3 Block codes for data transmission over DMCs(2/3)	Watch Online	MP4 Download
Chapter 4:Data Transmission and Channel Capacity 4.3 Block codes for data transmission over DMCs(3/3)	Watch Online	MP4 Download
Chapter 4:Data Transmission and Channel Capacity 4.5 Calculating channel capacity 4.5.1 Symmetric, Weakly Symmetric, and Quasi-symmetric Channels 4.5.2 Karuch-Kuhn-Tucker cond. for chan. capacity	Watch Online	MP4 Download
Chapter 4:Data Transmission and Channel Capacity 4.4 Example of Polar Codes for the BEC	Watch Online	MP4 Download
Chapter 4:Data Transmission and Channel Capacity 4.6 Lossless joint source-channel coding and Shannon’s separation principle	Watch Online	MP4 Download
Chapter 5：Differential Entropy and Gaussian Channels 5.1 Differential entropy	Watch Online	MP4 Download
Chapter 5：Differential Entropy and Gaussian Channels 5.1 Differential entropy 5.2 Joint & cond. diff. entrop., diverg. & mutual info	Watch Online	MP4 Download
Chapter 5：Differential Entropy and Gaussian Channels 5.3 AEP for continuous memoryless sources 5.4 Capacity for discrete memoryless Gaussian chan	Watch Online	MP4 Download
Chapter 5：Differential Entropy and Gaussian Channels 5.5 Capacity of Uncorrelated Parallel Gaussian Chan	Watch Online	MP4 Download
Chapter 5：Differential Entropy and Gaussian Channels 5.6 Capacity of correlated parallel Gaussian channels 5.7 Non-Gaussian discrete-time memoryless channels 5.8 Capacity of band-limited white Gaussian channel	Watch Online	MP4 Download
Chapter 6：Lossy Data Compression and Transmission 6.1.1 Motivation 6.1.2 Distortion measures 6.1.3 Frequently used distortion measures 6.2 Fixed-length lossy data compression	Watch Online	MP4 Download
Chapter 6：Lossy Data Compression and Transmission 6.3 Rate-distortion theorem AEP for distortion typical set Shannon’s lossy source coding theorem	Watch Online	MP4 Download
Chapter 6：Lossy Data Compression and Transmission 6.4 Calculation of the rate-distortion function 6.4.2 Rate distortion func / the squared error dist	Watch Online	MP4 Download
Chapter 6：Lossy Data Compression and Transmission 6.5 Lossy joint source-channel coding theorem 6.6 Shannon limit of communication systems(1/2)	Watch Online	MP4 Download
Chapter 6：Lossy Data Compression and Transmission 6.6 Shannon limit of communication systems(2/2)	Watch Online	MP4 Download
Preface and Introduction Chapter 1:Generalized Information Measures for Arbitrary Systems with Memory	Watch Online	MP4 Download
Chapter 2:General Data Compression Theorems	Watch Online	MP4 Download
Chapter 3:Measure of Randomness for Stochastic Processes	Watch Online	MP4 Download
Chapter 4:Channel Coding Theorems and Approximations of Output Statistics for Arbitrary Channels	Watch Online	MP4 Download

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