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Proportionate Robust Diffusion Recursive Least Exponential Hyperbolic Cosine Algorithm: Optimum Parameter Selection and Convergence Analysis
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DOI：10.1109/TCSII.2022.3215996.png)
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摘要
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In this brief, an improved version of the proportionate robust diffusion recursive least exponential hyperbolic cosine algorithm is suggested. This improved version is obtained by optimally selecting the step-size parameter of this algorithm using a minimization of the squared norm of the error vector. Moreover, a complete theoretical analysis of the presented algorithm is performed. This theoretical analysis consists of mean-square convergence analysis, mean-square steady-state analysis, and a discussion on the forgetting factor parameter selection. Moreover, simulation experiments show that the improved algorithm is superior than the original algorithm and other state-of-the-art algorithms in the literature in terms of speed of convergence.
Keyword:
Distributed estimation
proportionate
robust
exponential hyperbolic cosine
convergence analysis
parameter estimation
期刊
I
IF:
4.9
论文数:
8.8K
被引数:
2.5W
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PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
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SIGNAL PROCESSINGIF3.6
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