Artificial neural network

From Citizendium
Revision as of 20:19, 24 September 2007 by imported>Subpagination Bot (Add {{subpages}} and remove any categories (details))
Jump to navigation Jump to search
This article is developing and not approved.
Main Article
Discussion
Related Articles  [?]
Bibliography  [?]
External Links  [?]
Citable Version  [?]
 
This editable Main Article is under development and subject to a disclaimer.

Artificial Neural Networks (ANNs for short) are a connectionist processing model inspired on the biological neural networks. Artificial neural networks are composed by simple nodes called artificial neurons, in which the processing behavior is stored in the node interconnections as values called weights, which represent the strength of each neural connection, obtained after processing a sequence of patterns.

Adaptation and Learning

When a neuron receives and processes an input signal, it changes the weight value assigned to the input received. The weighted signals are summed to form the activation value, which is filtered by a function called transfer function. Changes in a specific neuron's behavior produces changes in the entire neural network, and this is basically how the neural networks learn.

See also