Journal Article10.4304/JCP.6.7.1511-1518
Study of Modulation Recognition Algorithm Based on Wavelet Transform and Neural Network
Yanfang Hou,Hongmei Feng +1 more
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TL;DR: The identification in category for FSK and PSK are simulated respectively, and the simulation results prove the approach proposed in this paper is efficient.
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Abstract: Modulation identification for communication signals has important applications both in military and civilian areas. Aimed at the non-stationary modulated signal of which signal to noise ratio (SNR) changes large, a novel method for recognition of modulation signals by wavelet transform and neural network theory is introduced. In this algorithm, instantaneous feature parameters of received signals are extracted using wavelet transform. Then, make singular value decomposition to the matrix which is composed of instantaneous parameters to get singular values. Error back propagation neural network (BPNN) with supervised training is to be made the classifier. The singular values obtained are used as feature vector and inputted to the classifier. So the automatic modulation recognition of signal is realized. The identification in category for FSK and PSK are simulated respectively, and the simulation results prove the approach proposed in this paper is efficient.
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References
Modulation classification of communication signals
Jiang Yuan,Zhang Zhao-yang,Qiu Pei-liang +2 more
- 31 Oct 2004
TL;DR: A novel algorithm using wavelet transform and pattern recognition to identify the modulation types of the communication signals automatically and is efficient at the SNR /spl les/ 15 dB.
50
A New Approach for Face Recognition Based on Singular Value Features and Neural Networks
Gan Jun-ying
- 01 Jan 2004
TL;DR: Repeated experimental results on ORL (Olivetti Research Laboratory) database demonstrate that under the conditions of large samples recognition method has the characteristics of simple realization, rapid recognition speed and high recognition rate, and also profits real-time realization.
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•Journal Article
Novel Method for Blind Recognition of Communication Signal Based on Time-frequency Analysis and Neural Network
TL;DR: In this paper, the authors presented a blind recognition method for blind recognition of communication signal to solve the problem of the classification and recognition in communication reconnaissance, where they used time-frequency analysis technology to extract the feature of the signals, and the neural network (backward propagation network) to class and recognize the signals.
2
Novel Method for Blind Recognition of Communication Signal Based on Time-frequency Analysis and Neural Network(WSANE2006)
Weihong Fu,Xiaoniu Yang,Xingwen Zeng,Naian Liu +3 more
- 03 Apr 2006
TL;DR: A novel method for blind recognition of communication signal to solve the problem of the classification and recognition in communication reconnaissance by using time-frequency analysis technology and the neural network to class and recognize the signals.
2