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New Directions in Statistical Signal Processing

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Haykin, Simon S. (EDT)/ Principe, Jose C. (EDT)/ Sejnowksi, Terrence J. (EDT)/ McWhirter, John (EDT) 作者
The MIT Press
譯者
2006-10-01 出版日期
544 頁數
USD 50.00 價格
Hardcover
叢書系列
9780262083485 圖書編碼

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New Directions in Statistical Signal Processing 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

New Directions in Statistical Signal Processing 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

New Directions in Statistical Signal Processing 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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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).

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