Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44001
標題: Fuzzy C-means based support vector machine for channel equalisation
作者: Juang, C.F.
莊家峰
Hsieh, C.D.
關鍵字: fuzzy clustering
fuzzy C-means
support vector machine
support
vectors
channel equalisation
classification
期刊/報告no:: International Journal of General Systems, Volume 38, Issue 3, Page(s) 273-289.
摘要: This paper proposes a new classification network, the fuzzy C-means based support vector machine (FCM-SVM) and applies it to channel equalisation. In contrast to a kernel-based SVM, the FCM-SVM has a smaller number of parameters while retaining the SVM's good generalisation ability. In FCM-SVM, input training data is clustered by FCM. The output of FCM-SVM is a weighted sum of the degrees where each input data belongs to the clusters. To achieve high generalisation ability, FCM-SVM weights are learned through linear kernel based SVM. Computer simulations illustrate the performance of the suggested network, where the FCM-SVM is used as a channel equaliser. Simulations with white Gaussian and coloured Gaussian noise are performed. This paper also compares simulation results from the FCM-SVM, the Gaussian kernel based SVM and the optimal equaliser.
URI: http://hdl.handle.net/11455/44001
ISSN: 0308-1079
文章連結: http://dx.doi.org/10.1080/03081070802128529
Appears in Collections:電機工程學系所

文件中的檔案:

取得全文請前往華藝線上圖書館



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.