The full text of this article


Fuzzy rule base reduction via singular value decomposition
by Hiyem Frikha-Djemel, Nabil Derbel
International Journal of Modelling, Identification and Control (IJMIC), Vol. 5, No. 4, 2008


Abstract: This paper deals with a fuzzy rule base reduction via Singular Value Decomposition (SVD). The method consists of forming a rule consequents matrix, applying SVD procedure and then keeping only the larger singular values. Hence, the dimension of the reduced rule base depends on the number of the retained singular values. New membership functions are obtained by generating linear combinations of the original ones. This approach is applicable regardless of the input variable's number, the inference paradigm and the shape of the initial membership functions. In this work, the SVD reduction is applied in the case of rule base where all fuzzy rules are defined and the case of rule set including some missing rules. Fuzzy Logic Controllers (FLCs) exploiting these rule bases are considered to control an inverted pendulum.

Online publication date: Wed, 25-Feb-2009


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email