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neural networks

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The term ‘Neural Network’ may refer either to a biological neural network or to an artificial neural network. The former is a network of biological neurons (electrically excitable cells that process and transmit electrical and chemical signals) interconnected within the nervous system. The latter is a mathematical, computational concept based on the results of observation of biological neural networks.

Artificial neural networks consist of groups of interconnected artificial neurons that receive one ore more inputs and perform simple operations on the data. The results are then selectively passed on to other neutrons, thus emulating the way biological neurons interact with each other.

There are many different models of neural networks. What they seem to have in common, however, is the learning factor. Through mimicking the biological model, the Artificial Networks are able to learn through processing the provided sample input.

Check out stackoverflow query for an extremely simple example of a neural network based on a tic-tac-toe game. Also, visit Neurosolutions for more valuable resources on the subject.

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About Jan Belezina