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

Houssam Hamici, Awos Kanan, Khalid Al-hammuri

2023BioMedInformatics10 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Finite impulse responseFilter designGenetic algorithmComputer scienceRoot-raised-cosine filterFilter (signal processing)Digital filterAdaptive filterAlgorithmHalf-band filterElectronic engineeringKernel adaptive filterSignal processingBandwidth (computing)Digital signal processingEngineeringComputer hardwareTelecommunicationsMachine learningComputer visionAdvanced Adaptive Filtering TechniquesBlind Source Separation TechniquesNeural Networks and Applications
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