Artificial neural network
An artificial neural network (ANN), also called a simulated neural network (SNN) or just a neural network (NN), is an interconnected group of artificial neurons that uses a mathematical or computational model for information processing based on a connectionist approach to computation. There is no precise agreed definition amongst researchers as to what a neural network is, but most would agree that it involves a network of relatively simple processing elements, where the global behaviour is determined by the connections between the processing elements and element parameters. The original inspiration for the technique was from examination of bioelectrical networks in the brain formed by neurons and their synapses (see biological neural network). In a neural network model, simple nodes (called variously "neurons", "neurodes", "PEs" ("processing elements") or "units") are connected together to form a network of nodes — hence the term "neural network".
Related Topics:
Artificial neuron - Connectionist - Brain - Synapse - Biological neural network - Nodes - Network
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~ Table of Content ~
| ► | Introduction |
| ► | Structure |
| ► | Advantages |
| ► | Applications |
| ► | Types of neural networks |
| ► | Relation to optimization techniques |
| ► | Related topics |
| ► | External links |
| ► | Bibliography |
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