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Tree-Like Multiple Neural Network Models Generator with a Complexity Estimation Based Decomposer

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4 Author(s)
Kurosh Madani ; Intelligence in Instrumentation and Systems division (I2S) of Image, Signal and Intelligent Systems Laboratory, Senart Institute of Technology, University PARIS XII, Av. Pierre Point, F-77127 Lieusaint, France, ; Abdennasser Chebira ; Mariusz Rybnik ; El-khier Bouyoucef

In this article we present a self-organizing hybrid modular approach that is aimed at reduction of processing task complexity by decomposition of an initially complex problem into a set of simpler sub-problems. This approach hybridizes artificial neural networks based artificial intelligence and complexity estimation loops in order to reach a higher level intelligent processing capabilities. In consequence, our approach mixtures learning, complexity estimation and specialized data processing modules in order to achieve a higher level self-organizing modular intelligent information processing system. Experimental results validating the presented approach are reported and discussed..

Published in:

2005 IEEE Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications

Date of Conference:

5-7 Sept. 2005