Description |
vi, 514 p. : ill. |
Series |
Neural information processing series |
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Neural information processing series.
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Bibliography |
Includes bibliographical references (p. [465]-508) and index. |
Contents |
Modeling the mind : from circuits to systems / Suzanna Becker -- Empirical statistics and stochastic models for visual signals / David Mumford -- The machine cocktail party problem / Simon Haykin, Zhe Chen -- Sensor adaptive signal processing of biological nanotubes (ion channels) at macroscopic and nano scales / Vikram Krishnamurthy -- Spin diffusion : a new perspective in magnetic resonance imaging / Timothy R. Field -- What makes a dynamical system computationally powerful? / Robert Legenstein, Wolfgang Maass -- A variational principle for graphical models / Martin J. Wainwright, Michael I. Jordan -- Modeling large dynamical systems with dynamical consistent neural networks / Hans-Georg Zimmermann ... [et al.] -- Diversity in communication : from source coding to wireless networks / Suhas N. Diggavi -- Designing patterns for easy recognition : information transmission with low-density parity-check codes / Frank R. Kschischang, Masoud Ardakani -- Turbo processing / Claude Berrou, Charlotte Langlais, Fabrice Seguin -- Blind signal processing based on data geometric properties / Konstantinos Diamantaras -- Game-theoretic learning / Geoffrey J. Gordon -- Learning observable operator models via the efficient sharpening algorithm / Herbert Jaeger ... [et al.]. |
Reproduction |
Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. |
Subject |
Neural networks (Neurobiology)
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Neural networks (Computer science)
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Signal processing -- Statistical methods.
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Neural computers.
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Genre/Form |
Electronic books.
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Added Author |
Haykin, Simon S., 1931-
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ProQuest (Firm)
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ISBN |
0262083485 (alk. paper) |
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9780262083485 (alk. paper) |
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