Artificial Neural Network

Vinod Patil

ISBN 10: 6200093415 / ISBN 13: 9786200093417

Verlag: LAP LAMBERT Academic Publishing Mai 2019, 2019

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 52 pp. Englisch.

Bestandsnummer des Verkäufers 9786200093417

Bibliografische Details

• Titel: Artificial Neural Network
• Verlag: LAP LAMBERT Academic Publishing Mai 2019
• Erscheinungsjahr: 2019
• Sprache: Englisch
• ISBN-10: 6200093415
• ISBN-13: 9786200093417
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 220B x 150 H x 4 T Millimeter Breite: 220 mm, Höhe: 150 mm, Tiefe: 4 mm
• Gewicht: 96 Gramm

Über diesen Titel

Inhaltsangabe

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.