New directions in statistical signal processing
New directions in statistical signal processing from systems to brain / [electronic resource] :
edited by Simon Haykin ... [et al.].
- Cambridge, Mass. : MIT Press, c2007.
- vi, 514 p. : ill.
- Neural information processing series .
- Neural information processing series. .
Includes bibliographical references (p. [465]-508) and index.
Modeling the mind : from circuits to systems / Empirical statistics and stochastic models for visual signals / machine cocktail party problem / Sensor adaptive signal processing of biological nanotubes (ion channels) at macroscopic and nano scales / Spin diffusion : a new perspective in magnetic resonance imaging / What makes a dynamical system computationally powerful? / variational principle for graphical models / Modeling large dynamical systems with dynamical consistent neural networks / Diversity in communication : from source coding to wireless networks / Designing patterns for easy recognition : information transmission with low-density parity-check codes / Turbo processing / Blind signal processing based on data geometric properties / Game-theoretic learning / Learning observable operator models via the efficient sharpening algorithm / Suzanna Becker -- David Mumford -- Simon Haykin, Zhe Chen -- Vikram Krishnamurthy -- Timothy R. Field -- Robert Legenstein, Wolfgang Maass -- Martin J. Wainwright, Michael I. Jordan -- Hans-Georg Zimmermann ... [et al.] -- Suhas N. Diggavi -- Frank R. Kschischang, Masoud Ardakani -- Claude Berrou, Charlotte Langlais, Fabrice Seguin -- Konstantinos Diamantaras -- Geoffrey J. Gordon -- Herbert Jaeger ... [et al.]. The A
Electronic reproduction.
Palo Alto, Calif. :
ebrary,
2013.
Available via World Wide Web.
Access may be limited to ebrary affiliated libraries.
GBA671791 bnb
Uk
Neural networks (Neurobiology)
Neural networks (Computer science)
Signal processing--Statistical methods.
Neural computers.
Electronic books.
QP363.3 / .N52 2007eb
612.8/2
Includes bibliographical references (p. [465]-508) and index.
Modeling the mind : from circuits to systems / Empirical statistics and stochastic models for visual signals / machine cocktail party problem / Sensor adaptive signal processing of biological nanotubes (ion channels) at macroscopic and nano scales / Spin diffusion : a new perspective in magnetic resonance imaging / What makes a dynamical system computationally powerful? / variational principle for graphical models / Modeling large dynamical systems with dynamical consistent neural networks / Diversity in communication : from source coding to wireless networks / Designing patterns for easy recognition : information transmission with low-density parity-check codes / Turbo processing / Blind signal processing based on data geometric properties / Game-theoretic learning / Learning observable operator models via the efficient sharpening algorithm / Suzanna Becker -- David Mumford -- Simon Haykin, Zhe Chen -- Vikram Krishnamurthy -- Timothy R. Field -- Robert Legenstein, Wolfgang Maass -- Martin J. Wainwright, Michael I. Jordan -- Hans-Georg Zimmermann ... [et al.] -- Suhas N. Diggavi -- Frank R. Kschischang, Masoud Ardakani -- Claude Berrou, Charlotte Langlais, Fabrice Seguin -- Konstantinos Diamantaras -- Geoffrey J. Gordon -- Herbert Jaeger ... [et al.]. The A
Electronic reproduction.
Palo Alto, Calif. :
ebrary,
2013.
Available via World Wide Web.
Access may be limited to ebrary affiliated libraries.
GBA671791 bnb
Uk
Neural networks (Neurobiology)
Neural networks (Computer science)
Signal processing--Statistical methods.
Neural computers.
Electronic books.
QP363.3 / .N52 2007eb
612.8/2