Angelov, Plamen and Filev, Dimitar
(2005)
Simpl_eTS: a simplified method for learning evolving Takagi-Sugeno fuzzy models.
In:
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on :.
IEEE, Reno, Las vegas, USA, pp. 1068-1073.
ISBN 0-7803-9159-4
Full text not available from this repository.
Abstract
This paper deals with a simplified version of the evolving Takagi-Sugeno (eTS) learning algorithm - a computationally efficient procedure for on-line learning TS type fuzzy models. It combines the concept of the scatter as a measure of data density and summarization ability of the TS rules, the use of Cauchy type antecedent membership functions, an aging indicator characterizing the stationarity of the rules, and a recursive least square algorithm to dynamically learn the structure and parameters of the eTS model. (c) IEEE Press
Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
"©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."
Uncontrolled Keywords:
/dk/atira/pure/core/keywords/computingcommunicationsandict
Subjects:
?? computing, communications and ictqa75 electronic computers. computer science ??
Deposited On:
11 Jan 2008 11:42
Last Modified:
16 Jul 2024 02:47