New directions in statistical signal processing : from systems to brain /
edited by Simon Haykin ... [et al.].
- 1 PDF (vi, 514 pages) : illustrations.
- Neural information processing series .
- Neural information processing series .
"Multi-User" Academic Complete Subscription 2011-2012
Includes bibliographical references (p. [465]-508) and index.
Restricted to subscribers or individual electronic text purchasers.
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).
Mode of access: World Wide Web
Access requires VIU IP addresses and is restricted to VIU students, faculty and staff.
Made available online by Ebrary.
9780262256315
Neural networks (Neurobiology)
Neural networks (Computer science)
Signal processing--Statistical methods.
Neural computers.
Neural Networks (Computer)
Algorithms.
Nerve Net.
Statistics as Topic.
Electronic books.
QP363.3 / .N52 2007eb
612.8/2
2006 N-993 WL 26.5 / N532 2007
"Multi-User" Academic Complete Subscription 2011-2012
Includes bibliographical references (p. [465]-508) and index.
Restricted to subscribers or individual electronic text purchasers.
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).
Mode of access: World Wide Web
Access requires VIU IP addresses and is restricted to VIU students, faculty and staff.
Made available online by Ebrary.
9780262256315
Neural networks (Neurobiology)
Neural networks (Computer science)
Signal processing--Statistical methods.
Neural computers.
Neural Networks (Computer)
Algorithms.
Nerve Net.
Statistics as Topic.
Electronic books.
QP363.3 / .N52 2007eb
612.8/2
2006 N-993 WL 26.5 / N532 2007