The Identification of ECG Signals Using WT-UKF and IPSO-SVM.

Li, Ning; Zhu, Longhui; Ma, Wentao; Wang, Yelin; He, Fuxing; Zheng, Aixiang; Zhang, Xiaoping

Li, Ning; Zhu, Longhui; Ma, Wentao; Wang, Yelin; He, Fuxing; Zheng, Aixiang; Zhang, Xiaoping.

Afiliação

Li N; School of Electrical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Zhu L; School of Electrical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Ma W; School of Electrical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Wang Y; School of Electrical Engineering, Xi'an University of Technology, Xi'an 710048, China.
He F; School of Electrical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Zheng A; School of Humanities and Foreign Languages, Xi'an University of Technology, Xi'an 710048, China.
Zhang X; Department of Electronic, Electrical, and Systems Engineering, School of Engineering, University of Birmingham, Birmingham B15 2TT, UK.

Sensors (Basel) ; 22(5)2022 Mar 02.

Article em En | MEDLINE | ID: mdl-35271105

Assuntos

Processamento de Sinais Assistido por Computador; Máquina de Vetores de Suporte; Algoritmos; Eletrocardiografia/métodos; Análise de Ondaletas

Palavras-chave

electrocardiogram identification; improved particle swarm optimization; parameter optimization; support vector machine; unscented Kalman filter; wavelet transform

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Sinais Assistido por Computador / Máquina de Vetores de Suporte Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

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