Neural Network Experiments on Personal Computers and Workstations
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Most neural network programs for personal computers simply control a set of fixed, canned network-layer algorithms with pulldown menus. This tutorial offers hands-on neural network experiments with a different approach. A simple matrix language lets users create their own neural networks and combine networks, and this software also permits combined simulation of neural networks together with other dynamic systems such as robots or physiological models. The enclosed student version of DESIRE/NEUNET differs from the full system only in the size of its data area and includes a screen editor, compiler, colour graphics, help screens, and ready-to-run examples. Users can also add their own help screens and interactive menus. The book provides an introduction to neural networks and simulation, a tutorial on the software, and many complete programs including several backpropagation schemes, creeping random search, competitive learning with and without adaptive-resonance function and conscience counterpropagation, nonlinear Grossberg-type neurons, Hopfield-type and bidirectional associative memories, predictors, function learning, biological clocks, system identification and more.
Format:Paperback
Language:English
ISBN:0262610736
ISBN13:9780262610735
Release Date:January 1991
Publisher:MIT Press (MA)
Length:248 Pages
Weight:1.18 lbs.
Dimensions:0.8" x 7.6" x 10.1"
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