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A method of designing nonlinear channel equalizer using conditional fuzzy c-means clustering

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4 Author(s)
Bum-Jin Oh ; Sch. of Electr. Eng., Chungbuk Nat. Univ., Cheongju, South Korea ; Keun-Chang Kwak ; Sung-Soo Kim ; Jeong-Woong Ryu

We propose a new method of designing a nonlinear channel equalizer using an adaptive neuro-fuzzy clustering method called a conditional fuzzy c-means. The structure identification of an adaptive neuro-fuzzy system is performed by the conditional fuzzy c-means clustering method with the homogeneous properties of the given input and output data. The parameter identification is established by hybrid learning using the back-propagation algorithm and recursive least squares estimation. Experimental results demonstrate that the proposed method improves the performance of the neuro-fuzzy system. Finally. we apply the proposed method to designing a nonlinear channel equalizer and obtain better results than previous methods.

Published in:

Signal Processing, 2002 6th International Conference on  (Volume:2 )

Date of Conference:

26-30 Aug. 2002