제어로봇시스템학회:학술대회논문집
- 2000.10a
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- Pages.366-366
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- 2000
Nonlinear Channel Equalization Using Adaptive Neuro-Fuzzy Fiter
적응 뉴로-퍼지 필터를 이용한 비선형 채널 등화
Abstract
In this paper, an adaptive neuro-fuzzy filter using the conditional fuzzy c-means(CFCM) methods is proposed. Usualy, the number of fuzzy rules exponentially increases by applying the grid partitioning of the input space, in conventional adaptive neuro-fuzzy inference system(ANFIS) approaches. In order to solve this problem, CFCM method is adopted to render the clusters which represent the given input and output data. Parameter identification is performed by hybrid learning using back-propagation algorithm and total least square(TLS) method. Finally, we applied the proposed method to the nonlinear channel equalization problem and obtained a better performance than previous works.
Keywords
- adaptive neuro-fuzzy filter;
- nonlinear channel equalization;
- conditional fuzzy c-means(CFCM);
- total least square(TLS);
- adaptive neuro-fuzzy inference system(ANFIS)