Introduction To The Theory Of Neural Computation, Volume I book
Par cornell robert le mardi, novembre 8 2016, 23:06 - Lien permanent
Introduction To The Theory Of Neural Computation, Volume I by Anders S. Krogh, John A. Hertz, Richard G. Palmer
Introduction To The Theory Of Neural Computation, Volume I Anders S. Krogh, John A. Hertz, Richard G. Palmer ebook
ISBN: 0201515601, 9780201515602
Page: 328
Publisher: Westview Press
Format: djvu
This thesis focusses on real-time computation of large neural networks using the Izhikevich spiking neuron model. Nunez, Neocortical Dynamics and Human EEG Rhythms (Oxford University Press, New York,. Wesley, Redwood City, CA, 1991). Based on event-driven computation, SpikeNet have reported successfully tracking and recognizing faces in real time without increasing computation burden. Gaito, Algorithmic Inference in Machine Learning, International Series on Advanced Intelligence, Vol. Hertz - Google Books The first chapters give a general introduction to the. John Hertz, Anders Krogh, and Richard G. (1987), Spin glass theory and beyond. Palmer, Introduction to the Theory of Neural Computation (Addison-. Axons and dendrites can be modelled using cable theory (Rall, 1959), while synapse. Introduction to the Theory of Neural Computation - John A. Pattern Recognition and Statistical Learning: Neural Networks: Machine Learning and Information Theory: Image Processing: Signal Processing: Books of Historical Interest . Palmer, Introduction to the Theory of Neural Computation, Addison Wesley Publ. Many disciplines from low-level biology through psychology and computer science. This book is a comprehensive introduction to the neural network models currently under intensive study for computational applications. 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.