商品簡介
Signal processing and neural computation have separately and significantly influencedmany disciplines, but the cross-fertilization of the two fields has begun only recently. Researchnow shows that each has much to teach the other, as we see highly sophisticated kinds of signalprocessing and elaborate hierachical levels of neural computation performed side by side in thebrain. In New Directions in Statistical Signal Processing, leading researchers from both signalprocessing and neural computation present new work that aims to promote interaction between the twodisciplines.The book's 14 chapters, almost evenly divided between signal processing and neuralcomputation, begin with the brain and move on to communication, signal processing, and learningsystems. They examine such topics as how computational models help us understand the brain'sinformation 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 tohidden Markov models (HMMs).
作者簡介
Simon Haykin is University Professor and Director of the Adaptive Systems Laboratory at McMaster University.
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