A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm

Pavankumar Ganjimala; Subrahmanyam Mula

doi:10.1109/ICECS58634.2023.10382870

A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm

Signal Processing 2024-01-17 v1

Authors: 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.

Keywords

fourier transform hardware acceleration matrix optimization and algorithms

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@article{arxiv.2310.10276,
  title  = {A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm},
  author = {Pavankumar Ganjimala and Subrahmanyam Mula},
  journal= {arXiv preprint arXiv:2310.10276},
  year   = {2024}
}

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To be published in the proceedings of the 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS 2023)

A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm

Abstract

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