Nonlinear Dynamical Systems
Feedforward Neural Network Perspectives
The first truly up-to-date look at the theory and capabilities of nonlinear dynamical systems that take the form of feedforward neural network structuresConsidered one of the most important types of structures in the study of neural networks and neural-like networks, feedforward networks incorporating dynamical elements have important properties and are of use in many applications. Specializing in experiential knowledge, a neural network stores and expands its knowledge base via strikingly human routes-through a learning process and information storage involving interconnection strengths known as synaptic weights.In Nonlinear Dynamical System…
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Produktdetails
Weitere Autoren: Lo, James T. / Fancourt, Craig L. / Principe, José C. / Katagiri, Shigeru / Haykin, Simon
- ISBN: 978-0-471-34911-2
- EAN: 9780471349112
- Produktnummer: 8678951
- Verlag: Wiley
- Sprache: Englisch
- Erscheinungsjahr: 2001
- Seitenangabe: 312 S.
- Masse: H23.9 cm x B17.4 cm x D2.3 cm 578 g
- Gewicht: 578
Über den Autor
IRWIN W. SANDBERG is a chaired professor at the University of Texas at Austin.JAMES T. LO teaches in the Department of Mathematics and Statistics, University of Maryland.CRAIG L. FANCOURT is a member of the Adaptive Image and Signal Processing Group at the Sarnoff Corp. in Princeton, New Jersey.JOSE C. PRINCIPE is BellSouth Professor in the Electrical and Computer Engineering Department at the University of Florida, Gainesville.SHIGERU KATAGIRI leads research on speech and hearing at NTT Communication Science Laboratories, Kyoto, Japan.SIMON HAYKIN teaches at McMaster University in Hamilton, Ontario, Canada. He has authored or coauthored over a dozen Wiley titles.
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