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A Gabor atom network for signal classification with application in radar target recognition

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2 Author(s)
Yu Shi ; Dept. of Autom., Tsinghua Univ., Beijing, China ; Xian-Da Zhang

A Gabor atom neural network approach is proposed for signal classification. The Gabor atom network uses a multilayer feedforward neural network structure, and its input layer constitutes the feature extraction part, whereas the hidden layer and the output layer constitute the signal classification part. From the physics point of view, it is shown that the time-shifted, frequency-modulated, and scaled Gaussian function is available for a basic model for the signal of high-resolution radar. Two experiment examples show that the Gabor atom network approach has a higher recognition rate in radar target recognition from range profiles as compared with several existing methods

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Signal Processing, IEEE Transactions on  (Volume:49 ,  Issue: 12 )