Step value-variable LMS (Least Mean Square) self-adaptation filtering algorithm and filter

A technology of adaptive filtering and step size, applied in the direction of adaptive network, impedance network, electrical components, etc., can solve the problems of large stable error value, small stable error value of filter, affecting system error performance, etc., and achieve a small steady state. Error value, small system stability error, effect of fast convergence speed

Inactive Publication Date: 2013-07-31
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0009] In the LMS filtering algorithm in the prior art, the algorithm step size is a fixed value, and a better filter convergence time and stable error value cannot be obtained at the same time
Specifically, when the step size u is set larger, the filter can quickly reach the convergence state, but if the filter is close to a stable

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  • Step value-variable LMS (Least Mean Square) self-adaptation filtering algorithm and filter
  • Step value-variable LMS (Least Mean Square) self-adaptation filtering algorithm and filter
  • Step value-variable LMS (Least Mean Square) self-adaptation filtering algorithm and filter

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Embodiment Construction

[0035] The specific implementation manner of the present invention will be further described below in conjunction with the drawings and embodiments. The following examples are only used to illustrate the present invention, but not to limit the scope of the present invention.

[0036] In this embodiment, at first a kind of LMS adaptive filtering algorithm with variable step size is provided, which mainly includes steps:

[0037] S1. The original signal is delayed and processed to obtain input signals corresponding to different delays;

[0038] S2. Adding the products of each input signal and its corresponding filter weight coefficient to obtain the output signal at this moment;

[0039] S3. Making a difference between the expected signal and the output signal to obtain an error value;

[0040] S4. Using the product of the error value, the step value, and the input signal as an instantaneous change to update the filter weight coefficient;

[0041] One of the greatest improvem...

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Abstract

The invention relates to the technical field of digital signal treatment, in particular to a step value-variable LMS (Least Mean Square) self-adaptation filtering algorithm and a step value-variable LMS (Least Mean Square) self-adaptation filter. According to the invention, since a step value capable of changing according to filtering stages can be supplied, a higher convergence rate and a smaller system stability error can be synchronously obtained, which shows that in the initial stage of self-adaptation filtering, a larger step value is provided, thereby obtaining a higher convergence rate, and a smaller step value is provided when the self-adaptation filtering approaches a stable state, so that a smaller stable state error value can be obtained.

Description

technical field [0001] The invention relates to the technical field of digital signal processing, in particular to a variable-step LMS (Least Mean Square, least mean square) adaptive filtering algorithm and filter. Background technique [0002] Adaptive filter has always been one of the research hotspots in the field of signal processing. After years of development, it has been widely used in digital communication, radar, sonar, seismology, navigation system, biomedicine and industrial control and other fields. [0003] The most widely used adaptive algorithm is the Least Mean Square (LMS, Least Mean Square) algorithm. The LMS algorithm is a search algorithm that simplifies the calculation of the gradient vector by properly adjusting the objective function. Due to its computational simplicity, the LMS algorithm and others related to it have been widely used in various applications of adaptive filtering. The basic idea of ​​the LMS algorithm is to adjust the weight coefficie...

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Application Information

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IPC IPC(8): H03H21/00
Inventor 张民黄宝起李启旺李青
Owner BEIJING UNIV OF POSTS & TELECOMM
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