NDLI: Characteristic recognition of pulse in frequency domain based on probabilistic neural network

Content Provider	IEEE Xplore Digital Library
Author	Yeqin Wang Lianghai Chen
Copyright Year	2011
Description	Author affiliation: Huaiyin Institute of Technology, Huai'an, China (Yeqin Wang; Lianghai Chen)
Abstract	In order to improve the level of automation for pulse signal processing and recognition, firstly, it used the fast Fourier transform with radix-2FFT algorithm to extract the characteristic parameters of pulse in frequency domain. Secondly, it made the dyadic discrete wavelet transform in four scales with MALLAT algorithm and calculated the detail energy values of four scales to constitute together the feature vector of pulse. Finally, for the shortcomings of traditional identification methods, the probabilistic neural network pulse identification method was proposed. It designed probabilistic neural network classifier and made the classification experiment, and the recognition rate was 93.00%. The results showed that the extracted feature vectors have a strong description capability of pulse.
Starting Page	116
Ending Page	118
File Size	215499
Page Count	3
File Format	PDF
ISBN	9781424494361
e-ISBN	9781424494392
DOI	10.1109/MACE.2011.5986871
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Continuous wavelet transforms Probabilistic Neural Network Wavelet transform Pulse Signal processing Probabilistic logic Discrete wavelet transforms Mathematical model Recognition
Content Type	Text
Resource Type	Article

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