New Directions in Statistical Signal Processing: From Systems to Brains (Neural Information Processing series) by Simon Haykin (PDF)

Description

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

User’s Reviews

Editorial Reviews: About the Author Simon Haykin is University Professor and Director of the Adaptive Systems Laboratory at McMaster University.José C. Príncipe is Distinguished Professor of Electrical and Biomedical Engineering at the University of Florida, Gainesville, where he is BellSouth Professor and Founder and Director of the Computational NeuroEngineering Laboratory.Terrence J. Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies and is a Distinguished Professor at the University of California, San Diego. He was a member of the advisory committee for the Obama administration’s BRAIN initiative and is President of the Neural Information Processing (NIPS) Foundation. He is the author of The Deep Learning Revolution (MIT Press) and other books.John McWhirter is Senior Fellow at QinetiQ Ltd., Malvern, Associate Professor at the Cardiff School of Engineering, and Honorary Visiting Professor at Queen’s University, Belfast.

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