Artificial neural network

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Revision as of 01:46, 5 July 2007 by imported>Felipe Ortega Gutiérrez
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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