Udvidet returret til d. 31. januar 2025

Artificial Neural Network

Artificial Neural Networkaf Vinod Patil
Bag om Artificial Neural Network

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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9786200093417
  • Indbinding:
  • Paperback
  • Sideantal:
  • 52
  • Udgivet:
  • 10. maj 2019
  • Størrelse:
  • 150x4x220 mm.
  • Vægt:
  • 96 g.
  • BLACK WEEK
Leveringstid: 2-3 uger
Forventet levering: 17. december 2024
Forlænget returret til d. 31. januar 2025

Beskrivelse af Artificial Neural Network

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.

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