artificial neural network

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artificial neural network

(artificial intelligence)
(ANN, commonly just "neural network" or "neural net") A network of many very simple processors ("units" or "neurons"), each possibly having a (small amount of) local memory. The units are connected by unidirectional communication channels ("connections"), which carry numeric (as opposed to symbolic) data. The units operate only on their local data and on the inputs they receive via the connections.

A neural network is a processing device, either an algorithm, or actual hardware, whose design was inspired by the design and functioning of animal brains and components thereof.

Most neural networks have some sort of "training" rule whereby the weights of connections are adjusted on the basis of presented patterns. In other words, neural networks "learn" from examples, just like children learn to recognise dogs from examples of dogs, and exhibit some structural capability for generalisation.

Neurons are often elementary non-linear signal processors (in the limit they are simple threshold discriminators). Another feature of NNs which distinguishes them from other computing devices is a high degree of interconnection which allows a high degree of parallelism. Further, there is no idle memory containing data and programs, but rather each neuron is pre-programmed and continuously active.

The term "neural net" should logically, but in common usage never does, also include biological neural networks, whose elementary structures are far more complicated than the mathematical models used for ANNs.

See Aspirin, Hopfield network, McCulloch-Pitts neuron.

Usenet newsgroup: news:comp.ai.neural-nets.
References in periodicals archive ?
Deep learning enables higher levels of recognition accuracy by capitalizing on the deeply layered structures of artificial neural networks in order to learn from prepared data.
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Artificial neural networks, computer programs that mimic the human brain, are great at learning patterns and sequences, but so far they've been limited in their ability to solve complex reasoning problems that require storing and manipulating lots of data.
Significant accumulated experience in development and implementation of the artificial neural networks makes it possible to get the skills of NN operation and start using it in practice after a relatively short period of time.
And then I was also fascinated with artificial neural networks,' he adds.
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But algorithms can be utilized to regulate the weights of the artificial neural networks in order to get the desired output from the nexus.

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