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arXiv · 2310.10276

A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm

Pavankumar Ganjimala·Subrahmanyam Mula
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Abstract

The high computation complexity of nonlinear adaptive filtering algorithms poses significant challenges at the hardware implementation level. In order to tackle the computational complexity problem, this paper proposes a novel block-oriented functional link adaptive filter (BO-FLAF) to model memoryless nonlinear systems. Through theoretical complexity analysis, we show that the proposed Hammerstein BO trigonometric FLAF (HBO-TFLAF) has 47% lesser multiplications than the original TFLAF for a filter order of 1024. Moreover, the HBO-TFLAF exhibits a faster convergence rate and achieved 3-5 dB lesser steady-state mean square error (MSE) compared to the original TFLAF for a memoryless nonlinear system identification task.

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Pavankumar Ganjimala, Subrahmanyam Mula. 2023-10-16. A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm. https://doi.org/10.1109/icecs58634.2023.10382870

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