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Title

State Analysis of Discrete-time Singular Nonlinear Systems Using a Fuzzy Neural Network

Year: 1384
COI: ICEE13_255
Language: EnglishView: 1,460
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Authors

Masoud Mirmomeni - Amirkabir University of Technology
Masoud Shafiee - Amirkabir University of Technology

Abstract:

Singular systems have been the subject of interest over the last two decades due to their many practical applications. On the other hand, there has been considerable interest in the application of intelligent technologies such as Artificial Neural Networks (ANN) and Fuzzy Logic in modeling complex phenomena, due to their innate nonlinear structures. This paper proposed an alternative neuro-fuzzy architecture for application to state analysis of singular nonlinear systems. The architecture employs an approximation to the fuzzy reasoning system to considerably reduce the dimension of the network as compared to similar approaches. Results not only demonstrate the advantages of the neuro-fuzzy approach, but it also highlight the advantages of the architecture for hardware realizations.

Keywords:

Paper COI Code

This Paper COI Code is ICEE13_255. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/42131/

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Mirmomeni, Masoud and Shafiee, Masoud,1384,State Analysis of Discrete-time Singular Nonlinear Systems Using a Fuzzy Neural Network,13th Iranian Conference on Electric Engineering,Zanjan,https://civilica.com/doc/42131

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