Work

A Low Complexity Block-oriented Functional Link Adaptive Filtering Algorithm

Year: 2023

Type: conference-paper

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.

Source: IEEE International Conference on Electronics, Circuits and Systems (ICECS)

DOI: 10.1109/icecs58634.2023.10382870

Authors: Pavankumar Ganjimala, Subrahmanyam Mula

Institution: Indian Institute of Technology Palakkad

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Ministry of Education, Ministry of Education, India

OpenAlex ID: W4390693208

FWCI: 1.067

Cites: 24

Cited by: 5

Related to: 10