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Volume 19 Issue 4
Jul.  1997
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Lian Bing, Wang Hongyu. RECURSIVE STRUCTURE AND QUASI-RECURSIVE STRUCTURE OF ADAPTIVE VOLTERRA FILTERS AND THEIR ALGORITHMS AND APPLICATIONS[J]. Journal of Electronics & Information Technology, 1997, 19(4): 476-482.
Citation: Lian Bing, Wang Hongyu. RECURSIVE STRUCTURE AND QUASI-RECURSIVE STRUCTURE OF ADAPTIVE VOLTERRA FILTERS AND THEIR ALGORITHMS AND APPLICATIONS[J]. Journal of Electronics & Information Technology, 1997, 19(4): 476-482.

RECURSIVE STRUCTURE AND QUASI-RECURSIVE STRUCTURE OF ADAPTIVE VOLTERRA FILTERS AND THEIR ALGORITHMS AND APPLICATIONS

  • Received Date: 1995-09-05
  • Rev Recd Date: 1996-09-04
  • Publish Date: 1997-07-19
  • 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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