Myocardial Ischemia Detection by Pulse Signal Features and Fuzzy Clustering

2008 ◽  
Author(s):  
Kang-Ming Chang ◽  
Zhi-Zhong Lin ◽  
Shing-Hong Liu ◽  
Chu-Chang Tyan
Keyword(s):  
Myocardial Ischemia ◽  
Fuzzy Clustering ◽  
Pulse Signal ◽  
Signal Features

scholarly journals An Intra-Pulse Modulation Type Recognition Algorithm for Radar Signals Based on the Improved Residual Network

2021 ◽  
Vol 2050 (1) ◽  
pp. 012009
Author(s):  
Fan Wang ◽  
Yifeng Huang ◽  
Ming Zhu ◽  
Jun Tang ◽  
Zhaohong Jia
Keyword(s):  
Loss Function ◽  
Pulse Signal ◽  
Recognition Algorithm ◽  
Radar Signal ◽  
Residual Network ◽  
Pulse Modulation ◽  
Time Frequency ◽  
Signal Features ◽  
Modulation Type ◽  
Radar Signals

Abstract For purpose of solve the problem of poor discrimination and robustness of intra-pulse signal features extracted by the traditional methods, this paper proposes a radar signal intra-pulse modulation type recognition algorithm based on the improved residual network. Firstly, one-dimensional time-domain radar signal is converted into two-dimensional time-frequency image by Smoothing Pseudo Wigner-Ville Distribution; Then the time-frequency image is preprocessed; ResNet-50 network is chosen as the framework. In order to retain the feature map information as much as possible, the convolution kernel is increased in the residual module. The cross entropy loss function and the center loss function are used as the loss function to speed up the convergence of the network. The improved residual network is used to realize the intra-pulse modulation type recognition of radar signal. The simulation experiments show that when the SNR is -14dB, the overall average recognition accuracy of the improved algorithm for eight kinds of radar signals (CM, LFM, NLFM, BLFM, BPSK, QPSK, OPSK, LFM+BPSK) can reach 97.29%, which shows the effectiveness.

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