Principles of Artificial Neural Networks

Principles of Artificial Neural Networks

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The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.This positive reinforcement is termed as adaptive resonance to motivate the resonance term in a€œARTa€. 9.2. (c) Gain and reset elements The gain elements feed the same scalar output to all neurons concerned as in Fig. 1, g1 being inputted toanbsp;...

Title:Principles of Artificial Neural Networks
Author:Daniel Graupe
Publisher:World Scientific - 2007-01-01


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