New directions in statistical signal processing : from systems to brain / edited by Simon Haykin [and others].

Format:

Book

Contributor:

Haykin, Simon S., 1931-

Series:

Neural information processing series

Language:

English

Subjects (All):

Neural networks (Neurobiology).

Neural networks (Computer science).

Signal processing--Statistical methods.

Signal processing.

Neural computers.

Physical Description:

1 online resource (vi, 514 pages) : illustrations.

Place of Publication:

Cambridge, Mass. : MIT Press, [2007]

System Details:

text file

Summary:

Signal processing and neural computation have separately and significantly influenced many disciplines, but the cross-fertilization of the two fields has begun only recently. Research now shows that each has much to teach the other, as we see highly sophisticated kinds of signal processing and elaborate hierachical levels of neural computation performed side by side in the brainches In New Directions in Statistical Signal Processing, leading researchers from both signal processing and neural computation present new work that aims to promote interaction between the two disciplines. The book's 14 chapters, almost evenly divided between signal processing and neural computation, begin with the brain and move on to communication, signal processing, and learning systems. They examine such topics as how computational models help us understand the brain's information processing, how an intelligent machine could solve the "cocktail party problem" with "active audition" in a noisy environment, graphical and network structure modeling approaches, uncertainty in network communications, the geometric approach to blind signal processing, game-theoretic learning algorithms, and observable operator models (OOMs) as an alternative to hidden Markov models (HMMs).

Contents:

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, 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, Wolfgang Maass 127

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

8 Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks / Hans-Georg Zimmermann, Ralph Grothmann, Anton Maximilian Schafer, 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, Masoud Ardakani 287

11 Turbo Processing / Claude Berrou, Charlotte Langlais, Fabrice Seguin 307

12 Blind Signal Processing Based on Data Geometric Properties / Konstantinos Diamantaras 337

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, Andreas Kolling 417.

Notes:

OCLC-licensed vendor bibliographic record.

ISBN:

9780262256315

0262256312

1429418737

9781429418737

OCLC:

77521428

Access Restriction:

Restricted for use by site license.