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Gradient variable step size lms adaptive filtering method

A technology of adaptive filtering and variable step size, applied in the direction of adaptive network, impedance network, electrical components, etc., can solve the problems of LMS algorithm steady-state error and algorithm convergence speed, so as to reduce steady-state error and improve convergence speed, effect of reducing the influence of noise

Active Publication Date: 2016-10-05
WUXI TONGCHUN NEW ENERGY TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a gradient variable step size LMS adaptive filtering method, which solves the problem that the steady-state error of the LMS algorithm and the improvement of the convergence speed of the algorithm are difficult to balance in the prior art

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  • Gradient variable step size lms adaptive filtering method
  • Gradient variable step size lms adaptive filtering method
  • Gradient variable step size lms adaptive filtering method

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Embodiment

[0048] In the simulation, the reference signal is a sinusoidal single input signal s=a*sin(0.05*pi*t), and zero-mean Gaussian white noise is added to the sinusoidal signal as the system input signal SNR=10dB; filter order m=128; sampling Number of points N=1000, drawing data is e 2 The result after Monte Carlo averaging of 100 times. Such as image 3 Shown, for the LMS algorithm when μ=0.001 and μ=0.0001, the convergence speed of the algorithm, it can be seen that the step size algorithm convergence speed is fast and the steady-state error is large, and the step size is small; the smoothing parameters of the algorithm proposed by the present invention are respectively: β=0.999, γ=1e-7, μ(0)=0.1. Figure 4 It is a comparison chart of the convergence speed curves of the GVSS-LMS algorithm and the LMS algorithm. It can be seen that the GVSS-LMS algorithm has a faster convergence speed and a lower steady-state error.

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Abstract

The steps of the gradient variable step size LMS adaptive filtering method of the present invention are: step 1, input signal X(n)={x(n), x(n-1),...,x(n-m+1)} is the signal vector formed by the delay at different times, x(n) is the sampling value of the first-order filter at time n, and m is the order of the transversal filter; step 2, multiply the input signal with the corresponding weight and calculate and, the actual output y(n) of the system is obtained, and the weight vectors are all initialized to 0; step 3, subtracting d(n) from y(n) to obtain the error signal e(n); step 4, obtaining the smooth gradient vector g( n); step 5, calculating the product of smooth gradient vectors at adjacent moments to obtain the iterative step size parameter at n moments; step 6, obtaining the weight vector at this moment; step 7, starting from step 1 to step 6 for cyclic calculation, iterative calculation output Serve. The method of the invention realizes rapid convergence without reducing the steady-state error.

Description

technical field [0001] The invention belongs to the technical field of adaptive signal processing, and relates to an LMS adaptive filtering method with gradient variable step size. Background technique [0002] As a branch of digital signal processing, adaptive filtering technology has been widely used in real life. Among them, the Least Mean Square (LMS) algorithm has become one of the most concerned algorithms in the practical use of adaptive filtering because of its simple implementation and robustness to signal statistical characteristics. However, the main shortcoming of the classic LMS algorithm is the contradiction between the convergence speed and the steady-state error, which seriously affects its application in some systems that require high convergence speed. The classic LMS algorithm uses a fixed step size, and the step size parameter μ controls the robustness, convergence speed and steady-state error of the algorithm. Generally, if the step size parameter is l...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H03H21/00
Inventor 席晓莉李敏超宋忠国
Owner WUXI TONGCHUN NEW ENERGY TECH
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