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A Block-Diagonal Recurrent Fuzzy Neural Network for Dynamic System Identification

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1 Author(s)
Mastorocostas, P.A. ; Technol. Educ. Inst. of Serres, Serres

A recurrent fuzzy neural network with internal feedback is suggested in this paper. The network is entitled Dynamic Block-Diagonal Fuzzy Neural Network (DBD-FNN), and constitutes a generalized Takagi-Sugeno-Kang fuzzy system, where the consequent parts of the fuzzy rules are small Block-Diagonal Recurrent Neural Networks. The proposed model is applied to a benchmark problem, where a dynamic system is to be identified. A comparative analysis with a series of recurrent fuzzy and neural models is conducted, highlighting the modeling characteristics of DBD-FNN.

Published in:
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International

Date of Conference: 23-26 July 2007

Page(s):
1 - 6
ISSN :
1098-7584
E-ISBN :
1-4244-1210-2
Print ISBN:
1-4244-1209-9
INSPEC Accession Number:
9795979
Conference Location :
London
Digital Object Identifier :
10.1109/FUZZY.2007.4295332
Product Type:
Conference Publications

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