標題: Adaptive Least Trimmed Squares Fuzzy Neural Network
作者: Chang, Jyh-Yeong
Liao, Shih-Hui
Lin, Chin-Teng
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: least trimmed squares (LTS) estimator;fuzzy neural network (FNN);least trimmed squares fuzzy neural network (LTS-FNN);adaptive least trimmed squares fuzzy neural network (ALTS-FNN)
公開日期: 2012
摘要: In this paper, we propose the adaptive least trimmed squares fuzzy neural network (ALTS-FNN), which applies the scale estimate to the least trimmed squares fuzzy neural network (LTS-FNN). The emphasis of this paper is particular on the robustness against the outliers and the choice of the trimming constant can be determined adaptively. Some numerical examples will be provided to compare the robustness against outliers for usual FNN and the ALTS-FNN. Simulation results show that the ALTS-FNN in the paper have good performance for outlier detection.
URI: http://hdl.handle.net/11536/23148
ISBN: 978-1-4673-2056-6
期刊: 2012 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY2012)
起始頁: 413
結束頁: 416
顯示於類別:會議論文