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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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Abstract
En 中文
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.
Keywords:
Distributed estimation
proportionate
robust
exponential hyperbolic cosine
convergence analysis
parameter estimation
Journal
I
IF:
4.9
Papers:
8.8K
Citations:
2.5W