Widely Linear Complex-Valued Least Mean M-Estimate Algorithms: Design and Performance Analysis

To utilize the full second-order statistical information of the complex-valued signal, a widely linear complex-valued LMM (WL-CLMM) algorithm is proposed by using different M-estimate functions. The proposed WL-CLMM algorithm can process both circular and noncircular complex-valued signals in impuls...

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Bibliographic Details
Published in:Circuits, systems, and signal processing Vol. 41; no. 10; pp. 5785 - 5806
Main Authors: Li, Lei, Pu, Yi-Fei
Format: Journal Article
Language:English
Published: New York Springer US 01.10.2022
Springer Nature B.V
Subjects:
Algorithms
Circuits and Systems
Design
Electrical Engineering
Electronics and Microelectronics
Engineering
Error signals
Instrumentation
Noise
Probability density functions
Random variables
Signal processing
Signal,Image and Speech Processing
Simulation
Statistical analysis
Complex-valued
Impulsive noise suppression
Adaptive filter
Widely linear
M-estimate
ISSN:0278-081X, 1531-5878
Online Access:Get full text
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Summary:To utilize the full second-order statistical information of the complex-valued signal, a widely linear complex-valued LMM (WL-CLMM) algorithm is proposed by using different M-estimate functions. The proposed WL-CLMM algorithm can process both circular and noncircular complex-valued signals in impulsive noise environments. Moreover, a novel adaptive threshold adjustment method for the M-estimate function is designed according to the probability density function of the complex-valued error signal. In addition, to decrease the sensitivity of the input signal to the performance of the algorithm, the normalized version of WL-CLMM (WL-CNLMM) has been developed. Then, we carry out the mean behavior and mean square behavior analysis of the proposed algorithms. Simulation results show that the proposed algorithms outperform some existing complex-valued algorithms and the theoretical results are well matched.
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ISSN:0278-081X
1531-5878
DOI:10.1007/s00034-022-02053-z