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Title

Decomposition and the principle of interaction prediction in hierarchical structure of learning algorithm of ANN

Authors

Year of publication

2015

Published in

Poznan University of Technology Academic Journals. Electrical Engineering

Journal year: 2015 | Journal number: Issue 84

Article type

scientific article

Publication language

english

Keywords
EN
  • artificial neural network
  • hierarchy
  • decomposition
  • coordination
  • coordination principle
Abstract

EN For the most popular ANN structure with one hidden layer, decomposition is done into two sub-networks. These sub-networks form the first level of the hierarchical structure. On the second level, the coordinator is working with its own target function. In the hierarchical systems theory three coordination strategies are defined. For the ANN learning algorithm the most appropriate is the coordination by the principle of interaction prediction. Implementing an off-line algorithm in all sub-networks makes the process of weight coefficient modification more stable. In the article, the quality and quantity characteristics of a coordination algorithm and the result of the learning algorithm for all sub-networks are shown. Consequently, the primary ANN achieves the global minimum during the learning process.

Pages (from - to)

113 - 120

Presented on

Computer Applications in Electrical Engineering 2015, 20-21.04.2015, Poznań, Poland

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public

Ministry points / journal

9

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