The Application of Hybrid Optimization For FIR Filter Design

Kaur, Harmandeep; Saini, Satish; Raut, Yudhishthir

doi:10.1109/ihcsp56702.2023.10127207

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2023

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“…Digital filters are widely used in many different fields to remove noise, to split multiple signals [1], for missing data imputation [2], and to enhance the quality of received signals [3,4]. In recent years, genetic algorithms (GA) have been increasingly used to optimize the design of digital filters because they can handle the issue of computational complexity and big data.…”

Section: Introduction 1problem Statementmentioning

confidence: 99%

Optimized FIR Filter Using Genetic Algorithms: A Case Study of ECG Signals Filter Optimization

Hamici,

Kanan,

Al-hammuri

2023

BioMedInformatics

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The advancement in technology and the availability of specialized digital signal processing chips have made digital filter design and implementation more feasible in a variety of fields, including biomedical engineering. This paper makes two key contributions. First, it uses a genetic algorithm to optimize the coefficients of finite impulse response (FIR) filters. Second, it conducts a case study on using genetic algorithms to optimize FIR filters for electrocardiogram (ECG) biomedical signal noise removal. The goal of the proposed filter design approach is to achieve the desired signal bandwidth while minimizing the side lobe level and eliminating unwanted signals using a genetic algorithm. The results of a comprehensive analysis show that the genetic algorithm-based filter is more effective than conventional filter designs in terms of noise removal efficiency.

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