A new approach to the P-wave detection and classification based upon application of wavelet neural network

Presents a new approach to the P wave classification problem which is based upon the application of a new recently developed and widely described tool such as the wavelet neural network. The novel idea of classification is based on the creation of our own non-standard wavelet exactly as a P wave morphology template and then calculation of the wavelet transform as a first layer of a classical multi-layer perceptron. This first layer works as a feature selector and extractor.

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