Interference Recognition Based on Singular Value Decomposition and Neural Network

Man FENG; Zinan WANG

doi:10.11999/JEIT190228

Volume 42 Issue 11

Nov. 2020

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Article Navigation > Journal of Electronics & Information Technology > 2020 > 42(11): 2573-2578

Man FENG, Zinan WANG. Interference Recognition Based on Singular Value Decomposition and Neural Network[J]. Journal of Electronics & Information Technology, 2020, 42(11): 2573-2578. doi: 10.11999/JEIT190228

Citation:

Man FENG, Zinan WANG. Interference Recognition Based on Singular Value Decomposition and Neural Network[J]. Journal of Electronics & Information Technology, 2020, 42(11): 2573-2578. doi: 10.11999/JEIT190228

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Interference Recognition Based on Singular Value Decomposition and Neural Network

doi: 10.11999/JEIT190228

Man FENG,
Zinan WANG^,

College of Information Science and Engineering, Southeast University, Nanjing 211189, China

Received Date: 2019-04-08
Rev Recd Date: 2020-03-03

Available Online: 2020-04-15

Publish Date: 2020-11-16

Abstract

Abstract

The anti-interference technology in wireless communication is great significance to the stability and security of communication. As an important part of anti-interference technology, interference recognition is a research hotspot. An interference recognition method based on singular value decomposition and neural network is proposed. This method only calculates the singular value of the signal matrix as the feature. Compared with the traditional method, it saves the computational complexity of multiple spectral features. The simulation results show that the recognition accuracy based on singular value decomposition and neural network is 10%~25% higher than the traditional method under the condition of jamming-signal ratio at 0 dB.
- Jamming recognition,
- Neural network,
- Singular value decomposition

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References(13)

References

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