Summary of Volume 1:Digital Communications 1
- Preface
- List of Acronyms
- Notations
- Introduction
- Chapter 1. Introduction to Information Theory
- 1.1. Introduction
- 1.2. Review of probabilities
- 1.3. Entropy and mutual information
- 1.4. Lossless source coding theorems
- 1.5. Theorem for lossy source coding
- 1.6. Transmission channel models
- 1.7. Capacity of a transmission channel
- 1.8. Exercises
- Chapter 2. Source Coding
- 2.1. Introduction
- 2.2. Algorithms for lossless source coding
- 2.3. Sampling and quantization
- 2.4. Coding techniques for analog sources with memory
- 2.5. Application to the image and sound compression
- 2.6. Exercises
- Chapter 3. Linear Block Codes
- 3.1. Introduction
- 3.2. Finite fields
- 3.3. Linear block codes
- 3.4. Decoding of binary linear block codes
- 3.5. Performances of linear block codes
- 3.6. Cyclic codes
- 3.7. Applications
- 3.8. Exercises
- Chapter 4. Convolutional Codes
- 4.1. Introduction
- 4.2. Mathematical representations and hardware structures
- 4.3. Graphical representation of the convolutional codes
- 4.4. Free distance and transfer function of convolutional codes
- 4.5. Viterbi's algorithm for the decoding of convolutional codes
- 4.6. Punctured convolutional codes
- 4.7. Applications
- 4.8. Exercises
- Chapter 5. Concatenated Codes and Iterative Decoding
- 5.1. Introduction
- 5.2. Soft input soft output decoding
- 5.3. LDPC codes
- 5.4. Parallel concatenated convolutional codes or turbo codes
- 5.5. Other classes of concatenated codes
- 5.6. Exercises
- Appendices
- Appendix A
- Appendix B
- Bibliography ...
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