Novel approach to design matched digital filter with Abelian group and fuzzy particle swarm optimization vector quantization

This paper presents a new method for designing matched digital filters with discrete valued coefficients. The fuzzy particle swarm optimization vector quantization (FPSOVQ) has been applied to obtain the optimum codebook in design of matched wavelet function.

Bibliographic Details
Authors: García Márquez, Fausto Pedro, Sharma, Bharat Bhushan, Kumar Sharma, Naveen, Banshwar, Anuj, Malik, Hasmat
Format: article
Publication Date:2023
Country:España
Institution:Universidad de Castilla-La Mancha
Repository:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/36295
Online Access:https://doi.org/10.1016/j.ins.2022.11.137
https://hdl.handle.net/10578/36295
Access Level:Open access
Keyword:Filter vector quantization
Group theory
Particle swarm optimization
Fuzzy inference method
Abelian group
Description
Summary:This paper presents a new method for designing matched digital filters with discrete valued coefficients. The fuzzy particle swarm optimization vector quantization (FPSOVQ) has been applied to obtain the optimum codebook in design of matched wavelet function.

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