Includes bibliographical references (p. [465]-508) and index.
Contents:
Learning observable operator models via the efficient sharpening algorithm / Herbert Jaeger ... [et al.]. Empirical statistics and stochastic models for visual signals / David Mumford -- A 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.].
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.