Sigma-if neural network as the use of selective attention technique in classification and knowledge discovery problems solving
Abstract
The article presents the most important properties of Sigma-if neuron and neural network, which use a selective attention technique to solve classification problems. Abilities of Sigma-if neuron to perform active aggregation of input signals and to solve linearly inseparable problems are discussed. Variety of conducted experiments, during which Sigma-if network was compared with multilayer perceptron, are also presented. These experiments show benefits from using Sigma-if network instead of MLP, both in classification problems solving and in knowledge discovery from data.
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PDFDOI: http://dx.doi.org/10.17951/ai.2006.5.1.121-131
Date of publication: 2006-01-01 00:00:00
Date of submission: 2016-04-27 10:15:51
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