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- W4387479827 abstract "This paper proposes an improved proportionate arctangent framework that relies on a least mean square/fourth (IPALMS/F) algorithm for the physical sparse system identification problem. The ALMS/F algorithm has significant robustness against impulsive noise, whereas the improved proportionate concept when utilized with the ALMS/F takes advantage of the sparse characteristic to increase convergence time. Finally, the IPALMS/F algorithm is implemented using a recursive adaptive sparse exponential functional link neural network (RASETFLN) nonlinear filter and is named the RASETFLN-IPALMS/F algorithm which resulted in enhanced performance compared to other existing filters in terms of robustness in an impulsive environment, convergence rate, and steady-state error for system identification and acoustic echo cancellation." @default.
- W4387479827 created "2023-10-11" @default.
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- W4387479827 date "2023-11-01" @default.
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- W4387479827 title "An improved proportionate arctangent framework based LMS/F algorithm for system identification" @default.
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- W4387479827 doi "https://doi.org/10.1016/j.apacoust.2023.109668" @default.
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