Application of Volterra LMS Adaptive Filter Algorithm Based on Gaussian Distribution
This paper mainly studied the LMS adaptive filter algorithm to the Volterra system model. Through the construction of the second order Volterra system model, the application of respectively selecting the first order and second order variable step length de-correlation Volterra LMS algorithm in gaussian noise environment, when the input signals in different correlation coefficient, the iteration times are not more than 2000 times and all items can realize the convergence, which prove the accuracy of the algorithm paper presented. The Volterra LMS adaptive filter algorithm can be effectively applied into the mechanical vibration damping and noise elimination, which has a broad application prospect.
Keywords: olterra series, adaptive filter algorithm, LMS, system identification, gaussian distribution.
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ABOUT THE AUTHORS
Xinling Wen
Xinling Wen received the Master degree in data collection and signal processing from North China University of Water Resources and Electric Power, in 2009. Currently, she is a Lecturer at Zhengzhou Institute of Aeronautical Industry Management. Her interests are in data collection and signal processing and nonlinear system modeling.
Dongfang Luo
Henan College of Finance & Taxation
Xinling Wen
Xinling Wen received the Master degree in data collection and signal processing from North China University of Water Resources and Electric Power, in 2009. Currently, she is a Lecturer at Zhengzhou Institute of Aeronautical Industry Management. Her interests are in data collection and signal processing and nonlinear system modeling.
Dongfang Luo
Henan College of Finance & Taxation
