scholarly journals Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks

PLoS ONE ◽  
2020 ◽  
Vol 15 (7) ◽  
pp. e0234068
Author(s):  
Hui Li ◽  
Ming Li
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Convolutional Neural Networks ◽  
Recognition Algorithm ◽  
Pattern Recognition Algorithm ◽  
Modulation Signal

TRANSITION TO CONVOLUTIONAL NEURAL NETWORKS IN RADAR PROBLEMS

2019 ◽  
pp. 96-99
Author(s):  
K. Maystrenko ◽  
A. Budilov ◽  
D. Afanasev
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Target Detection ◽  
Convolutional Neural Networks ◽  
Network Topology ◽  
Subject Areas ◽  
The Subject ◽  
Printed Materials ◽  
Hardware Costs

Goal. Identify trends and prospects for the development of radar in terms of the use of convolutional neural networks for target detection. Materials and methods. Analysis of relevant printed materials related to the subject areas of radar and convolutional neural networks. Results. The transition to convolutional neural networks in the field of radar is considered. A review of papers on the use of convolutional neural networks in pattern recognition problems, in particular, in the radar problem, is carried out. Hardware costs for the implementation of convolutional neural networks are analyzed. Conclusion. The conclusion is made about the need to create a methodology for selecting a network topology depending on the parameters of the radar task.

Research on Modulation Recognition Algorithm of Digital Communication Signal Based on Wavelet Denoising

2014 ◽  
Vol 608-609 ◽  
pp. 459-467 ◽  
Author(s):  
Xiao Yu Gu
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Decision Theory ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Modulation Recognition ◽  
The Core ◽  
Feature Parameters ◽  
Communication Signal ◽  
Modulation Signal

The paper researches a recognition algorithm of modulation signal and modulation modes. The modulation modes to be recognized include 2ASK, 2FSK, 2PSK, 4ASK, 4FSK and 4PSK modulation. There are two methods recognizing modulation modes of digital signal, method based on decision theory and pattern-recognition method based on feature extraction. The method based on decision theory is not suitable for recognition with multiple modulation modes. The core of pattern recognition based on feature extraction is selection of feature parameters. So the paper uses the feature parameters with simple calculation, easy to be implemented and high recognition rate as the core. The extraction of feature parameters is based on instant feature of modulation signal after Hilbert transformation.

Sign in / Sign up

Export Citation Format

Share Document