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Research of automatic detection of ECG based on quantum neural networks with multiresolution analysis / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 480-483, 2009.
Article in Chinese | WPRIM | ID: wpr-280172
ABSTRACT
An automatic detection of Electrocardiogram (ECG) using Quantum Neural Networks (QNN) with multiresolution analysis is given in the paper. QNN originates from exploiting BP neural networks. With the quantum neurons, QNN can model the levels of uncertainty arising from complex classification problems. Its potential advantage over conventional methods is based on the argument for reliability. The fuzzy feature is expected to enhance the reliability of the network, which is critical for improving desirable diagnosis accuracy. And wavelet transform with multiresolution analysis is adopted in ECG pretreatment for reducing the numbers of neurons. So it can improve convergence speed of the network. The results of simulation confirmed the feasibility of the proposed approach.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Quantum Theory / Signal Processing, Computer-Assisted / Pattern Recognition, Automated / Neural Networks, Computer / Electrocardiography / Methods Type of study: Diagnostic study Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2009 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Quantum Theory / Signal Processing, Computer-Assisted / Pattern Recognition, Automated / Neural Networks, Computer / Electrocardiography / Methods Type of study: Diagnostic study Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2009 Type: Article