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Introduction To The Theory Of Neural Computation,
Introduction To The Theory Of Neural Computation,

Introduction To The Theory Of Neural Computation, Volume I. Anders S. Krogh, John A. Hertz, Richard G. Palmer

Introduction To The Theory Of Neural Computation, Volume I


Introduction.To.The.Theory.Of.Neural.Computation.Volume.I.pdf
ISBN: 0201515601,9780201515602 | 328 pages | 9 Mb


Download Introduction To The Theory Of Neural Computation, Volume I



Introduction To The Theory Of Neural Computation, Volume I Anders S. Krogh, John A. Hertz, Richard G. Palmer
Publisher: Westview Press




[7] Hertz, J., Krogh, A., Palmer, R. Palmer, Introduction to the Theory of Neural Computation, Addison Wesley Publ. Introduction to the Theory of Neural Computation. Neural computation has been described as “ embarrassingly parallel” as each neuron can be thought of as spike frequency and spike volume is proposed and used to evaluate the system. This thesis focusses on real-time computation of large neural networks using the Izhikevich spiking neuron model. Introduction to the theory of neural computation. Axons and dendrites can be modelled using cable theory (Rall, 1959), while synapse. John Hertz, Anders Krogh, and Richard G. Gaito, Algorithmic Inference in Machine Learning, International Series on Advanced Intelligence, Vol. Addison-Wesley, Redwood City, CA. First of all, when we are talking about a neural network, we *should* usually better say "artificial neural network" (ANN), because that is what we mean most of the time. Many disciplines from low-level biology through psychology and computer science. Pattern Recognition and Statistical Learning: Neural Networks: Machine Learning and Information Theory: Image Processing: Signal Processing: Books of Historical Interest .

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