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.

Detalles Bibliográficos
Autores: García Márquez, Fausto Pedro, Sharma, Bharat Bhushan, Kumar Sharma, Naveen, Banshwar, Anuj, Malik, Hasmat
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/36295
Acceso en línea:https://doi.org/10.1016/j.ins.2022.11.137
https://hdl.handle.net/10578/36295
Access Level:acceso abierto
Palabra clave:Filter vector quantization
Group theory
Particle swarm optimization
Fuzzy inference method
Abelian group
Descripción
Sumario: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.

Similares en LA Referencia