1 volume (various pagings) : illustrations ; 28 cm
CONTENTS NOTE
Text of Note
Network objects, data, and training styles --;Multilayer networks and backpropagation training --;Dynamic netowkrs --;Control systems --;Radial bias networks --;Self-organizing learning vector quantization networks --;Adaptive filters and adaptive training --;Advanced topics --;Historical networks --;Network object reference --;Mathematical notation --;Blocks for the simulink environment --;Code notes.
SUMMARY OR ABSTRACT
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A collection of algorithms, functions and apps to create, train, visualize, and simulate neural networks. Functions include classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control.