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Dynamical Systems with Saturation Nonlinearities

Analysis and Design
BuchKartoniert, Paperback
197 Seiten
Englisch
Springererschienen am28.07.1994
Procedures and results are determined which constitute the first successful synthesis procedure for associative memories by means of artificial neural networks with arbitrarily pre-specified full or partial interconnecting structure and with or without symmetry constraints for the connection matrix.mehr

Produkt

KlappentextProcedures and results are determined which constitute the first successful synthesis procedure for associative memories by means of artificial neural networks with arbitrarily pre-specified full or partial interconnecting structure and with or without symmetry constraints for the connection matrix.
ZusammenfassungThis three-part monograph addresses topics in the areas of control systems, signal processing and neural networks. Procedures and results are determined which constitute the first successful synthesis procedure for associative memories by means of artificial neural networks with arbitrarily pre-specified full or partial interconnecting structure and with or without symmetry constraints for the connection matrix.

Inhalt/Kritik

Inhaltsverzeichnis
to dynamical systems with saturation nonlinearities.- Qualitative theory of control systems with control constraints and state saturation: Two fundamental issues.- Asymptotic stability of dynamical systems with state saturation.- Null controllability of discrete-time dynamical systems with control constraints and state saturation.- Stability analysis of one-dimensional and multidimesional state-space digital filters with overflow nonlinearities.- Criteria for the absence of overflow oscillations in fixed-point digital filters using generalized overflow characteristics.- Stability analysis of state-space realizations for multidimensional filters with overflow nonlinearities.- to part III.- Analysis and synthesis of a class of neural networks with piecewise linear saturation activation functions.- Sparsely interconnected neural networks for associative memories with applications to cellular neural networks.- Robustness analysis of a class sparsely interconnected neural networks with applications to design problem.mehr

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