Artificial Neural Network - Patil, Vinod;Jaware, Tushar;Badgujar, Ravindra
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An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems…mehr

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Produktbeschreibung
An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well. Neural network simulations appear to be a recent development. However, this field was established before the advent of computers, and has survived several eras. Many important advances have been boosted by the use of inexpensive computer emulations.
Autorenporträt
Herr Patil Vinodkumar Ramesh arbeitet als Assistenzprofessor in der E&TC Abteilung des RCPIT Shirpur und hat 13 Jahre Lehrerfahrung. Er hat ein Studium der Elektronik und ein Aufbaustudium in digitaler Elektronik abgeschlossen.