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Variable step size sparse augmented complex adaptive filter

An adaptive filter and variable step size technology, which is applied in the direction of adaptive network, impedance network, electrical components, etc., can solve the problems of slow convergence speed and large misalignment, and achieve faster convergence speed, low steady-state misalignment, and enhanced identification effect of ability

Pending Publication Date: 2020-11-03
SUZHOU UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

However, there are two problems as follows: 1) When estimating sparse systems, the convergence speed is slow or the misalignment is large; 2) Due to the use of a fixed step size, the adaptive filter needs to be between fast convergence speed and low steady-state misalignment. compromise

Method used

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  • Variable step size sparse augmented complex adaptive filter
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Embodiment

[0022] The present embodiment adopts the method verification VSS-1 of computer experiment 0 - Performance of the ACNLMS filter. Use the VSS-1 proposed by this application in the experiment 0 -ACNLMS filter for sparse unknown system identification in the context of non-circular input signals and compares its performance with ACNLMS and l 0 -ACNLMS and VSS-ACNLMS adaptive filter performance are compared. As a special case of this application, when VSS-l 0 - When the step size of ACNLMS adopts a fixed value, the filter is abbreviated as l 0 -ACNLMS; when l 0 - ACNLMS does not use l 0 When the norm is constrained, the filter is abbreviated as ACNLMS. The VSS-1 realized in the implementation mode of this application 0 -ACNLMS adaptive filter identification sparse unknown system includes the following steps:

[0023] 1) Through the expected signal d at time n n and augmented input vector u n Calculate the error signal e of the adaptive filter n ,Right now in, is the a...

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Abstract

The invention discloses a variable step size sparse augmented complex self-adaptive filter, and belongs to the field of digital filter design. The filter comprises a sparse regularized augmented normalized minimum mean square filter and a variable step size adaptive updating part. A sparse regularization augmentation normalization minimum mean square self-adaption method is adopted, so the self-adaption filter can obtain a higher convergence speed, the variable step size method solves the compromise limitation of the convergence speed and steady-state imbalance, the higher convergence speed can be obtained, and lower steady-state imbalance can also be obtained. The variable step size sparse augmented complex self-adaptive filter disclosed by the invention can be applied to electronic communication equipment such as a stereo echo canceller and the like.

Description

technical field [0001] The invention discloses an adaptive filter, in particular a variable step size sparse augmented complex adaptive filter, which belongs to the field of digital filter design. Background technique [0002] In the application of system identification, there are some unknown systems in which most of the coefficients of the unknown vectors are zero, while a small number of coefficients are non-zero values. Such systems are called sparse systems. In reality, such situations are relatively common. For example, echo cancellation scenarios. If the general adaptive filter is used to estimate the unknown sparse system, it will cause problems such as slow convergence speed or large steady-state imbalance. [0003] Yuantao Gu et al. proposed a low-order norm-constrained adaptive filter [l 0 -norm constraintLMS algorithm for sparse system identification, IEEE Signal Processing Letters, 2009, 16:774-777], its steady state offset is lower than the least mean square...

Claims

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Application Information

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IPC IPC(8): H03H21/00
CPCH03H21/0043
Inventor 倪锦根宗玉莲
Owner SUZHOU UNIV
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