Cooperative and Graph Signal Processing: Principles and Applications (Paperback)

1. Adaptation and learning 2. Detection, estimation and filtering 3. Bayesian approach to inference 4. Optimization and control 5. Machine learning 6. Game-theoretic learning 7. Discrete-time signal processing 8. Sampling and recovery of graph signals 9. Design of graph filters and filter banks 10. Statistical signal processing 11. Inference of graph topology 12. Prediction and learning 13. Monitoring and sensing 14. Optimal network signal processing and resource allocation 15. Network security and privacy 16. Cooperative and coordinated multi-cell techniques 17. Source and channel decoding 18. Scheduling and queuing protocols 19. Learning, distributed decision-making, estimation, and filtering 20. Consensus and coordination 21. Dynamic social networks 22. Information diffusion and rumor spreading 23. Multi-layered social networks 24. Marketing and advertising, trend prediction, recommendation systems, and crowdsourcing 25. Genomics and systems biology 26. Media and video 27. Smart grids 28. Internet of Things 29. Wireless health 30. Neuroscience