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Artificial neural networks on the base of neural-like computational units have many applications and are intensively used for solving numerous important practical tasks. It is common that the threshold unit is incapable solving many rather easy recognition tasks. The using of neurons with more complicated activation functions allowed surmounting this constrain. Although there were multi-threshold...
The increase of the functional possibilities of neural elements is important in the synthesis of neural network schemes that are used to implement complex mappings that arise in various problems of classification, form/pattern recognition, time lines prognostication, etc. This article introduces the concept of generalized neural element with the threshold activation function.
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