Sigma-if neural network as the use of selective attention technique in classification and knowledge discovery problems solving

Maciej Huk

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.

Full Text:

PDF


DOI: http://dx.doi.org/10.17951/ai.2006.5.1.121-131
Data publikacji: 2006-01-01 00:00:00
Data złożenia artykułu: 2016-04-27 10:15:51


Statistics


Total abstract view - 191
Downloads (from 2020-06-17) - PDF - 0

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2015 Annales UMCS Sectio AI Informatica

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.