Advanced Bayesian Signal Processing

Introduction.- Part I: Bayesian Parameter Estimation for Wireless Communications and Sensing.- Bayesian Decision Theory: A Unified Framework for Parameter Estimation.- Point Estimators.- Bayesian Estimators.- Expectation Maximization.- Factor Graph and Message Passing.- Subspace Methods.- Part II: Sparse Bayesian Inference (Compressive Sensing) for Wireless Communications and Sensing.- Introduction to Compressive Sensing (CS).- Optimization Based CS Recovery Algorithms.- Greedy CS Recovery Algorithms.- Approximate Message Passing.- Sparse Bayesian Learning.- Variational Bayesian Inference.- Part III: Advanced Topics in Future Wireless Networks.- Structure Compressive Sensing with Dynamic Grid.- Turbo Compressive Sensing.- Dynamic Bayesian Learning.- Advanced Variational Bayesian Inference Methods.- Bayesian Deep Learning.- Conclusion.