An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversa...An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.展开更多
基金Supported by the National Natural Science Foundation of China(60772056)the Postdoctoral Science Foundation of China(20070421094)
文摘An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.
