New Directions in Statistical Signal Processing - Table of Contents

October 2006
8 x 10, 544 pp., 149 illus.
$50.00/£37.95 (CLOTH)
Short

ISBN-10:
0-262-08348-5
ISBN-13:
978-0-262-08348-5

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New Directions in Statistical Signal Processing
From Systems to Brains
Edited by Simon Haykin, José C. Príncipe, Terrence J. Sejnowski and John McWhirter

	Series Foreword	vii

1.	Modeling the Mind: From Circuits to Systems Suzanna Becker	1

2.	Empirical Statistics and Stochastic Models for Visual Signals David Mumford	23

3.	The Machine Cocktail Party Problem Simon Haykin and Zhe Chen	51

4.	Sensor Adaptive Signal Processing of Biological Nanotubes (Ion Channels) at Macroscopic and Nano Scales Vikram Krishnamurthy	77

5.	Spin Diffusion: A New Perspective in Magnetic Resonance Imaging Timothy R. Field	119

6.	What Makes a Dynamical System Computationally Powerful? Robert Legenstein and Wolfgang Maass	127

7.	A Variational Principle for Graphical Models Martin J. Wainwright and Michael I. Jordan	155

8.	Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks Hans-Georg Zimmermann, Ralph Grothmann, Anton Maximilian Schäfer and Christoph Tietz	203

9.	Diversity in Communication: From Source Coding to Wireless Networks Suhas N. Diggavi	243

10.	Designing Patterns for Easy Recognition: Information Transmission with Low-Density Parity-Check Codes Frank R. Kschischang and Masoud Ardakani	287

11.	Turbo Processing Claude Berrou, Charlotte Langlais and Fabrice Seguin	307

12.	Blind Signal Processing Based on Data Geometric Properties Konstantinos Diamantaras	379

13.	Game-Theoretic Learning Geoffrey J. Gordon	379

14.	Learning Observable Operator Models via the Efficient Sharpening Algorithm Herbert Jaeger, Mingjie Zhao, Klaus Kretzschmar, Tobias Oberstein, Dan Popovici and Andreas Kolling	417

	References	465

	Contributors	509

	Index Sample Chapter - Download PDF (34 KB)	513

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