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A proportional control and normalized lmp filtering method under cim function

A proportional control and normalization technology, applied in the direction of adaptive network, electrical components, impedance network, etc., can solve the problem of slow convergence speed of LMP algorithm, achieve the effect of wide application range, guarantee filtering accuracy and convergence speed

Active Publication Date: 2019-08-27
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

Since the overall convergence speed of the algorithm is determined by the convergence speed of the smaller weight components, the convergence speed of the LMP algorithm is slowed down by the small components in the sparse channel.

Method used

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  • A proportional control and normalized lmp filtering method under cim function
  • A proportional control and normalized lmp filtering method under cim function
  • A proportional control and normalized lmp filtering method under cim function

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Embodiment Construction

[0033] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following description.

[0034] Such as figure 1 As shown, a proportional control and normalized LMP filtering method under a CIM function, including the following steps:

[0035] S1. The input signal x(n) of the adaptive filter=[x(n),x(n-1),...,x(n-M+1)] T Optimal weight vector with filter expectation Multiply, plus the noise signal v(n), to get the desired output signal d(n):

[0036] d(n)=w o T x(n)+v(n);

[0037] In the formula, M represents the channel length;

[0038] S2. The input signal x(n) of the adaptive filter=[x(n),x(n-1),...,x(n-M+1)] T And filter real-time weight vector w(n)=[w 1 (n),w 2 (n),...,w M (n)] T Multiply to get the real-time output signal y(n):

[0039] y(n)=w(n) T x(n);

[0040] S3. Make a difference between the expected ou...

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Abstract

The invention discloses a proportional control and normalized LMP filtering method under the CIM function, comprising the following steps: multiplying the input signal of the adaptive filter with the optimal weight vector of the filter, adding the noise signal, and obtaining the expected output Signal; multiply the input signal and the real-time weight vector of the filter to obtain the real-time output signal; make the difference between the expected output signal and the real-time output signal to obtain the signal error; design the cost function of the filtering algorithm according to the minimum mean square p-norm criterion; introduce Proportional step size control matrix, the weight update equation is obtained by the steepest descent method and normalized; the CIM function is introduced to optimize the proportional step size control matrix, so that each weight component can obtain a corresponding step size factor; the adaptive filter The weights are updated iteratively. The invention can ensure the filtering accuracy and convergence speed of the self-adaptive filtering method, even when the channel sparsity becomes smaller, it can still maintain better filtering accuracy and convergence speed.

Description

technical field [0001] The invention relates to the technical field of digital signal processing, in particular to a proportional control and normalized LMP filtering method under the CIM function. Background technique [0002] The adaptive filter is a filter that tracks the time-varying characteristics of the signal by changing the parameters of the traditional filter through an adaptive algorithm. The traditional filter needs to know the channel structure, but many channels are unknown in actual situations, and the adaptive filter The filter can adaptively find the optimal filter parameters in an iterative manner according to the statistical characteristics of the signal or noise without knowing the system structure. This feature makes the adaptive filter echo cancellation and channel equalization in the communication field , filtering and inverse filtering, system identification, noise elimination, etc. have been widely used. The least mean square p-norm algorithm (Least...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H03H21/00
Inventor 石颖张静静张洪斌赵集毛翔
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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