title: [A wavelet neural network algorithm of EEG signals data compression and spikes recognition].
abstract: A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.
authors.affiliation: Department of Computer Science, Wuhan University of Technology, Wuhan 430070.
authors.forename: Y
authors.initials: Y
authors.lastname: Zhang
authors.forename: A
authors.initials: A
authors.lastname: Liu
authors.forename: K
authors.initials: K
authors.lastname: Yu
mesh_terms: D000328:Adult; D000465:Algorithms; D002648:Child; D004569:Electroencephalography; D004827:Epilepsy / Q000175:diagnosis / Q000503:physiopathology*; D006801:Humans; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted