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
CN103227623AInactive Publication Date: 2013-07-31BEIJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
BEIJING UNIV OF POSTS & TELECOMM
Publication Date
2013-07-31
Estimated Expiration
Not applicable · inactive patent

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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.
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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...

Claims

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