Neural Networks And Fuzzy Systems: A Dynamical Systems Approach To Machine Intelligence

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The text combines the related fields of neural networks and fuzzy systems_from the theoretical level of first principles and the applications level of new adaptive fuzzy systems in control and signal processing. The book develops neural networks as both trainable dynamical systems and stochastic gradient systems, focusing on principles of learning, self-organization and stability. Table Of Contents Foreword by Lotfi A. Zadeh. Foreword by James A. Anderson. Preface. Neural Networks and Fuzzy Systems. NEURAL NETWORK THEORY Neuronal Dynamics I: Activations and Signals. Neuronal Dynamics II: Activation Models. Synaptic Dynamics Unsupervised Learning. Synaptic Dynamics II Supervised Learning. Architectures and Equilibria. ADAPTIVE FUZZY SYSTEMS Fuzziness Versus Probability Fuzzy Associative Memories.v Comparison of Fuzzy and Neural Truck Backer-Upper Control Systems. Fuzzy Image Transform Coding. Comparison of Fuzzy and Kalman-Filter Target-Tracking Control Systems. Appendix: Neural and Fuzzy Software Instructions. Index.