.png){kind=icon}
Return
Widely linear complex-valued hyperbolic secant adaptive filtering algorithm and its performance analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2023.109146.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
To achieve good estimation in the impulsive noise environment, some hyperbolic functions have been introduced as cost functions to develop robust adaptive filtering algorithms in recent years. However, the hyperbolic functions have rarely been studied for complex-valued signals. In this paper, a robust adaptive algorithm is introduced for processing both circular and non-circular complex-valued signals by utilizing the complex hyperbolic secant cost functions. Moreover, its performance is thoroughly analyzed, including mean convergence, mean-square transient behavior, and mean-square steady-state behavior. Finally, the simulation results show the advantages of the proposed algorithm for complex-valued signal processing in non-Gaussian environments and verify the accuracy of the theoretical performance analysis.& COPY; 2023 Elsevier B.V. All rights reserved.
Keywords:
Impulsive noise suppression
Complex -valued signal
Widely linear
Hyperbolic function
Journal
IF:
3.6
Papers:
10.0K
Citations:
1.7W
Organization
Cited Papers
Selective partial-update augmented complex-valued LMS algorithm and its performance analysis.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
ShareSaveA robust diffusion recursive generalized modified Blake-Zisserman algorithm for distributed estimation under an adaptive kernel widthSIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
ShareSaveShareSaveShareSaveShareSave
ShareSaveShareSave
View more