Proportional control and normalized LMP filtering method under CIM function

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

Active Publication Date: 2018-09-07
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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  • Proportional control and normalized LMP filtering method under CIM function
  • Proportional control and normalized LMP filtering method under CIM function
  • 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 a CIM function. The method comprises the following steps: multiplying an input signal of an adaptive filter byan optimal weight vector of the filter, and adding a noise signal to obtain a desired output signal; multiplying the input signal by a real-time weight vector of the filter to obtain a real-time output signal; performing subtraction on the desired output signal and the real-time output signal to obtain a signal error; designing a cost function of a filtering algorithm according to the least mean square p-norm criterion; importing a proportional step size control matrix, obtaining an update equation of the weight via a steepest descent method, and performing normalization processing; importingthe CIM function to optimize the proportional step size control matrix, so that each weight component obtains a corresponding step factor; and performing iterative update on the weight of the adaptivefilter. By adoption of the proportional control and normalized LMP filtering method disclosed by the invention, the filtering precision and the convergence speed of the adaptive filtering method canbe guaranteed, and even when the sparsity of the channel becomes small, relatively good filtering precision and convergence speed can still be maintained.

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 Applications(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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