Variable step-size pseudo affine projection algorithm for censored regression

The censored observations of adaptive signal processing have widely occurred in plenty of utility applications. Using traditional adaptive algorithms to recognize systems will confront convergence reduced under these circumstances. To address the above problem, the least mean square algorithm for ce...

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Bibliographic Details
Published in:Signal, image and video processing image and video processing, 2023-11, Vol.17 (8), p.4229-4234
Main Authors: Wang, Bolin, Wen, Pengwei, Qu, Boyang, Song, Xiaowei, Liu, Kai, Chai, Xuzhao, Sun, Jun, Mu, Xiaomin
Format: Article
Language:English
Subjects:
Adaptive algorithms
Computer Imaging
Computer Science
Convergence
Image Processing and Computer Vision
Multimedia Information Systems
Original Paper
Pattern Recognition and Graphics
Regression
Signal processing
Signal,Image and Speech Processing
System identification
Vision
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Summary:The censored observations of adaptive signal processing have widely occurred in plenty of utility applications. Using traditional adaptive algorithms to recognize systems will confront convergence reduced under these circumstances. To address the above problem, the least mean square algorithm for censored regression (CR-LMS) has been proposed. However, the CR-LMS algorithm will converge slowly under colored inputs. In this paper, a pseudo affine projection algorithm based on censored regression (CR-PAP) is present to process colored input signals. Moreover, the variable step-size strategy is used to enhance the convergence performance. Computer simulations verify the better convergence of the proposed algorithm over the CR-LMS algorithm in system identification scenarios.
ISSN:1863-1703
1863-1711
DOI:10.1007/s11760-023-02655-3