title: [Research of automatic detection of ECG based on quantum neural networks with multiresolution analysis].
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.
authors.affiliation: Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China. wsylcq@163.com
authors.forename: Shuyan
authors.initials: S
authors.lastname: Wang
authors.forename: Yusong
authors.initials: Y
authors.lastname: Wang
mesh_terms: D004562:Electrocardiography / Q000295:instrumentation* / Q000379:methods; D006801:Humans; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011789:Quantum Theory; D012815:Signal Processing, Computer-Assisted