New Directions in Statistical Signal Processing: From Systems to Brains

Simon Haykin, José C. Príncipe, Terrence J. Sejnowski, John McWhirter9780262083485, 0262083485

Leading researchers in signal processing and neural computation present work aimed at promoting the interaction and cross-fertilization between the two fields.

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Table of contents :
Contents……Page 6
Series Foreword……Page 8
Preface……Page 10
1 Modeling the Mind: From Circuits to Systems……Page 12
2 Empirical Statistics and Stochastic Models for Visual Signals……Page 34
3 The Machine Cocktail Party Problem……Page 62
4 Sensor Adaptive Signal Processing of Biological Nanotubes (Ion Channels) at Macroscopic and Nano Scales……Page 88
5 Spin Di.usion: A New Perspective in Magnetic Resonance Imaging……Page 130
6 What Makes a Dynamical System Computationally Powerful?……Page 138
7 A Variational Principle for Graphical Models……Page 166
8 Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks……Page 214
9 Diversity in Communication: From Source Coding to Wireless Networks……Page 254
10 Designing Patterns for Easy Recognition: Information Transmission with Low-Density Parity-Check Codes……Page 298
11 Turbo Processing……Page 318
12 Blind Signal Processing Based on Data Geometric Properties……Page 348
13 Game-Theoretic Learning……Page 390
14 Learning Observable Operator Models via the Efficient Sharpening Algorithm……Page 428
References……Page 476
Contributors……Page 520
Index……Page 524