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    Dynamical Systems with Saturation Nonlinearities

    Analysis and Design

    AvDerong Liu,Anthony N. Michel

    Häftad, Engelska, 1994

    Del 195 i serien Lecture Notes in Control and Information Sciences

    544 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    This 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.

    Produktinformation

    • Utgivningsdatum:1994-07-28
    • Mått:155 x 235 x 12 mm
    • Vikt:330 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Lecture Notes in Control and Information Sciences
    • Antal sidor:197
    • Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
    • ISBN:9783540198888

    Utforska kategorier

    • Elektronik och kommunikationer inom Naturvetenskap och teknik
    • Systemvetenskap och AI inom Data och IT
    • Beräkning och matematisk analys inom Naturvetenskap och teknik

    Innehållsförteckning

    • 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.
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