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Titolo:
A gabor atom network for signal classification with application in radar target recognition
Autore:
Shi, Y; Zhang, XD;
Indirizzi:
Tsing Hua Univ, Dept Automat, Beijing 100084, Peoples R China Tsing Hua Univ Beijing Peoples R China 100084 ng 100084, Peoples R China Xidian Univ, Key Lab Radar Signal Proc, Xian, Peoples R China Xidian UnivXian Peoples R China dar Signal Proc, Xian, Peoples R China
Titolo Testata:
IEEE TRANSACTIONS ON SIGNAL PROCESSING
fascicolo: 12, volume: 49, anno: 2001,
pagine: 2994 - 3004
SICI:
1053-587X(200112)49:12<2994:AGANFS>2.0.ZU;2-J
Fonte:
ISI
Lingua:
ENG
Soggetto:
TIME-FREQUENCY DICTIONARIES; RANGE PROFILES; NEURAL-NETWORK; TRANSFORM; REPRESENTATION;
Keywords:
adaptive signal representation; feature extraction; Gabor transform; neural networks; radar target recognition; signal classification; time-frequency analysis;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
--discip_EC--
Citazioni:
28
Recensione:
Indirizzi per estratti:
Indirizzo: Shi, Y Microsoft Res China, Beijing, Peoples R China Microsoft Res China Beijing Peoples R China ing, Peoples R China
Citazione:
Y. Shi e X.D. Zhang, "A gabor atom network for signal classification with application in radar target recognition", IEEE SIGNAL, 49(12), 2001, pp. 2994-3004

Abstract

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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Documento generato il 29/03/20 alle ore 08:37:14