Also referred to as connectionist architectures, parallel distributed processing, and neuromorphic systems, artificial neural networks are information-processing paradigms inspired by the way the densely interconnected, parallel structure of the mammalian brain processes information.
Artificial neural networks are collections of mathematical models that emulate some of the observed properties of biological nervous systems and draw on the analogies of adaptive biological learning.
The key element of the ANN paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements that are analogous to neurons and are tied together with weighted connections that are analogous to synapses .
In other words, ANN try to simulate the biological neural networks and to reproduce ultimately the human way of thinking, with the final goal of producing human-like machines, or even ultimately machines which perform better than humans.
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