This volume studies information theory, communication systems, and circuit models.
This volume studies information theory, communication systems, and circuit models. It connects probability, signal processing, and networked systems.
Part I. Foundations of Information Theory
Chapter 1. Information Measures
1.1 Entropy 1.2 Joint and conditional entropy 1.3 Mutual information 1.4 Relative entropy 1.5 Examples
Chapter 2. Source Coding
2.1 Data compression 2.2 Prefix codes 2.3 Huffman coding 2.4 Limits of compression 2.5 Examples
Chapter 3. Channel Capacity
3.1 Communication channels 3.2 Capacity definition 3.3 Noisy channels 3.4 Coding theorems (overview) 3.5 Examples
Part II. Communication Systems
Chapter 4. Signals and Systems
4.1 Continuous and discrete signals 4.2 Linear time-invariant systems 4.3 Convolution 4.4 Frequency analysis 4.5 Examples
Chapter 5. Modulation Techniques
5.1 Amplitude modulation 5.2 Frequency modulation 5.3 Phase modulation 5.4 Digital modulation 5.5 Examples
Chapter 6. Noise and Detection
6.1 Noise models 6.2 Signal-to-noise ratio 6.3 Detection theory 6.4 Estimation 6.5 Examples
Part III. Coding Theory
Chapter 7. Error-Correcting Codes
7.1 Linear codes 7.2 Hamming codes 7.3 Distance properties 7.4 Applications 7.5 Examples
Chapter 8. Advanced Coding
8.1 Convolutional codes 8.2 Turbo codes (overview) 8.3 LDPC codes 8.4 Applications 8.5 Examples
Chapter 9. Decoding Algorithms
9.1 Maximum likelihood decoding 9.2 Iterative decoding 9.3 Complexity considerations 9.4 Applications 9.5 Examples
Part IV. Signal Processing
Chapter 10. Fourier Analysis
10.1 Fourier series 10.2 Fourier transform 10.3 Discrete Fourier transform 10.4 Fast Fourier transform 10.5 Examples
Chapter 11. Filtering
11.1 Linear filters 11.2 Frequency response 11.3 Digital filters 11.4 Applications 11.5 Examples
Chapter 12. Sampling Theory
12.1 Sampling theorem 12.2 Reconstruction 12.3 Aliasing 12.4 Applications 12.5 Examples
Part V. Circuits and Systems
Chapter 13. Circuit Elements
13.1 Resistors, capacitors, inductors 13.2 Circuit laws 13.3 Network analysis 13.4 Applications 13.5 Examples
Chapter 14. Analog Circuits
14.1 Amplifiers 14.2 Filters 14.3 Oscillators 14.4 Applications 14.5 Examples
Chapter 15. Digital Circuits
15.1 Logic gates 15.2 Sequential circuits 15.3 Memory systems 15.4 Applications 15.5 Examples
Part VI. Networks and Communication
Chapter 16. Network Models
16.1 Graph representations 16.2 Routing 16.3 Flow control 16.4 Applications 16.5 Examples
Chapter 17. Wireless Communication
17.1 Channel models 17.2 Multipath propagation 17.3 MIMO systems 17.4 Applications 17.5 Examples
Chapter 18. Information Networks
18.1 Network coding 18.2 Distributed communication 18.3 Applications 18.4 Examples 18.5 Connections
Part VII. Applications
Chapter 19. Data Transmission
19.1 Internet protocols 19.2 Data encoding 19.3 Compression 19.4 Applications 19.5 Examples
Chapter 20. Multimedia Systems
20.1 Audio and video coding 20.2 Streaming 20.3 Compression standards 20.4 Applications 20.5 Examples
Chapter 21. Communication Devices
21.1 Sensors 21.2 Embedded systems 21.3 Communication hardware 21.4 Applications 21.5 Examples
Part VIII. Research Directions
Chapter 22. Advanced Topics
22.1 Quantum information 22.2 Network information theory 22.3 Machine learning for communication 22.4 Modern developments 22.5 Emerging areas
Chapter 23. Open Problems
23.1 Capacity of complex networks 23.2 Efficient coding 23.3 Noise limits 23.4 Computational challenges 23.5 Future directions
Chapter 24. Historical and Conceptual Notes
24.1 Development of information theory 24.2 Key contributors 24.3 Evolution of communication systems 24.4 Cross-disciplinary impact 24.5 Summary
Appendix
A. Information theory formulas B. Coding tables C. Proof techniques checklist D. Signal processing identities E. Cross-reference to other MSC branches