自适应Volterra滤波器的递归结构和类递归结构及其算法和应用
RECURSIVE STRUCTURE AND QUASI-RECURSIVE STRUCTURE OF ADAPTIVE VOLTERRA FILTERS AND THEIR ALGORITHMS AND APPLICATIONS
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摘要: 本文参考自适应IIR滤波器理论,提出了自适应Volterra滤波器(AVF)的递归结构和类递归结构,讨论了其特点和应用范围.递归结构的引入可显著减少AVF的参数和计算量.本文还给出了类递归结构AVF的在线辨识算法和在非线性系统辨识中的应用;给出了递归结构AVF的滤波算法和在非线性相关噪声抵消中的应用.在仿真实验中,将上述算法与多层感知器和非递归结构AVF做了对比.结果表明,本文算法住性能和计算量上均有明显优势。Abstract: In reference of the theory of adaptive IIR filters, the paper puts forward the recursive structure and quasi-recursive structure of Adaptive Volterra Filters(AVF), and discusses their characteristics and areas of applications. The introduction of recursive structure can remarkably reduce the parameters and computational cost of AVF. The on-line identification algorithm of quasi-recursive structure AVF with its application in non-linear system identification and the filtering algorithm of recursive structure AVF with its application in non-linear correlated noise cancellation are also given. In simulations, the above algorithms are compared with multi-layered perceptron and non-recursive AVF. The results show the algorithms of the paper have obvious advantages both in performance and in computational cost.
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Sandberg I W. On Volterra expansions for time-varying nonlinear systems. IEEE Trans. on Circuit[2]and Syst.,1983, CAS-30.(2): 61-67.[3]罗发龙,李衍达.神经网络与信号处理.北京:电子工业出版,1993.[4]Sbynk J J. Adaptive IIR filtering. IEEE Signal Processing Mag.,1989,6(2): 4-21.[5]Piche S P. Steepest descent algorithms for neural controllers and filters. IEEE Trans. on Neural Networks, 1994, NN-5:198-212.
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