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The BPANN is essentially a network of simple processing nodes arranged into different layers as input, hidden and the output.
An artificially neural network usually consists of a large amount of simple processing units, namely neurons, via mutual interconnection.
The spatial warping algorithm is mapped onto a linear array of simple processing elements with each element of a particular segment communicating with its nearest neighbours.
Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements.
The model is characterized by a network of three layers of simple processing units connected by acyclic links (Fig. 1).
A neural network is an information processing system consisting of a large number of simple processing elements called neurons.
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The impact of simpler processing strategies on cost efficiency is worthy of future investigation.
The finding underscores the idea that, in a situation in which the non-occurrence of reward may or may not have behavioral relevance, as in our task, the electrocortical response to the behaviorally relevant absence of an outcome overrides the effect of the simple processing of a disadvantageous outcome.
Actually an artificial neural network (ANN) is an enormously interconnected network structure comprising of several simple processing elements proficient of executing parallel computation for data processing.
Indeed an ANN is a massively interconnected network structure consisting of many simple processing elements capable of performing parallel computation for data processing.
Indeed an artificial neural network is a massively interconnected network structure consisting of many simple processing elements capable of performing parallel computation for data processing.
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