Modifications of intensifiers and fuzzy neuronal receptive fields: algorithmic developments and applications-MIMO case

Authors:
Mohamed S. Ibrahim
Affiliations:
Knowledge Based Systems and Robotic Department, Mubarak City for Scientific Research and Technology Applications, Alexandria, Egypt
Venue:
CONTROL'05 Proceedings of the 2005 WSEAS international conference on Dynamical systems and control
Year:
2005

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Abstract

In this paper modifications of intensifiers have been done for the injection into the receptive field of the fuzzy neural networks. Algorithmic developments for these modifiers are carried out for single-input single-output (SISO) as well as for multi-input multi-output (MIMO) fuzzy neural networks. This work can be beneficial for applications in different fields such as image processing, pattern recognition, control engineering, etc. The effects of the modified intensifiers on the localized fuzzy receptive field strengths as well as the overall performances of the fuzzy neural networks have been studied. Simulation results have been presented using complex nonlinear dynamical system (MIMO Case study) suffering from uncertainties. Also, comparative studies with previous works have been given, exhibit improved performances using the proposed technique.