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《Journal of Data Acquisition and Processing》 2011-05
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Hybrid Blind Equalization Algorithm Based on Genetic Algorithm and Wavelet Transform

Guo Yecai,Fan Kang,Xu Wencai,Xu Fang(College of Electronic & Information Engineering,Nanjing University of Information Science & Technology,Nanjing,210044,China)  
Constant modulus algorithm(CMA) has slow convergence speed and easily immerges in partial minimum owing to the lack of initialization theory.Aiming at these disadvantages,hybrid blind equalization algorithm based on genetic algorithm and wavelet transform(GAWT-CMA) is proposed to improve the performance of CMA.The proposed hybrid algorithm is formed by embeding WT-CMA in normal genetic algorithm.It uses the global convergence of genetic operator to conduct a macro-search,and conducts micro-search with WT-CMA.It obtains a better initialization weight vector in overall range with a little bit of data by the hybrid algorithm,and then gets globally optimal solution by WT-CMA.Computer simulation with underwater acoustic channel shows that GAWT-CMA's convergence is about 9 000 times faster than CMA,about 3 000 times faster than WT-CMA,and its steady-state error is smaller than CMA by 3 dB,smaller than WT-CMA by about 1 dB.
【Fund】: 全国优秀博士学位论文作者专项资金(200753)资助项目;; 安徽省高等学校自然科学基金(KJ2010A096)资助项目;; 江苏省自然科学基金(BK2009410)资助项目;; 江苏省高等学校自然科学基金(08KJB510010)资助项目;; 江苏省六大人才高峰基金(2008026)资助项目;; 江苏省高校优势学科“传感网与现代气象装备”资助项目
【CateGory Index】: TN911.5
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