NDLI: Learning analysis for correlation of fuzzy rules in applying RLS for neural fuzzy systems

Content Provider	IEEE Xplore Digital Library
Author	Jen-Wei Yeh Shun-Feng Su
Copyright Year	2012
Description	Author affiliation: Dept. of Electrical Engineering, National Taiwan University of science and Technology, Taiwan (Jen-Wei Yeh; Shun-Feng Su)
Abstract	It is well-known that Self-constructing neural fuzzy inference network (SONFIN) is a nice fuzzy inference system that has been equipped with structure learning capability. For the learning mechanisms, SONFIN can either be employed with the adaptive learning algorithm from neural network, which is often called backpropagation (BP) learning algorithm or use the Recursive Least Squares (RLS) algorithm in finding the parameters in the consequence part. In this paper, we reported the analysis on the use of RLS algorithm for neural fuzzy systems under the structure of SONFIN. Such a RLS algorithm is originally proposed to learn parameters in the consequence part only for TSK fuzzy systems. RLS has been demonstrated to be capable of providing great learning performance to neural fuzzy systems. From our previous work, it can be observed that the advantages of using RLS over BP and various issues, such as forgetting factor or reset operation are also investigated. All the above studies are based on the use of the full covariance matrixin the RLS algorithm. However, such an approach may result in heavy computational burden especially when the rule number is large. An alternative approach is to neglect the correlation among rules. In this study, we will report our analyses on the effects of correlation among rules. In order to have a clear demonstration on those effects, some special designs for the system are considered. From our study, it is clearly evidence that such neglect may results in large errors.
Starting Page	609
Ending Page	613
File Size	786261
Page Count	5
File Format	PDF
ISBN	9781467323109
e-ISBN	9781467323116
DOI	10.1109/GrC.2012.6468690
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computational modeling Inference algorithms Covariance matrix
Content Type	Text
Resource Type	Article

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