Research on Modulation Recognition Method of MSK Signals Based on Wavelet Transform

2014 ◽  
Author(s):  
Yongxin Feng ◽  
Xiaoyu Zhang ◽  
Bo Qian ◽  
Guangshen Li
Keyword(s):  
Wavelet Transform ◽  
Modulation Recognition ◽  
Recognition Method

scholarly journals Deep Learning-Based Automatic Modulation Recognition Method in the Presence of Phase Offset

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 42841-42847 ◽  
Author(s):  
Jie Shi ◽  
Sheng Hong ◽  
Changxin Cai ◽  
Yu Wang ◽  
Hao Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Modulation Recognition ◽  
Recognition Method ◽  
Phase Offset ◽  
Automatic Modulation Recognition

Activity Recognition via Feature Decomposition

2011 ◽  
Vol 243-249 ◽  
pp. 6221-6224
Author(s):  
Qing Wei ◽  
Hao Zhang ◽  
Zhi Jing Liu
Keyword(s):  
Wavelet Transform ◽  
Feature Detection ◽  
Markov Models ◽  
Hidden Markov ◽  
Haar Wavelet ◽  
Human Motion ◽  
Feature Points ◽  
Recognition Method ◽  
Haar Wavelet Transform ◽  
Coupled Hidden Markov Models

This paper presents a new recognition method for human motion, which is represented by Haar wavelet transform and recognized by Coupled Hidden Markov Model. We tackle the challenge of detecting the feature points by Haar wavelet transform to improve the accuracy. We extract binary silhouette after creating the background model. Then the low-level features are detected by Haar wavelet and principal vectors in two subspaces are obtained. We utilize Coupled Hidden Markov Models to model and recognize them, and demonstrate their usability. Compared with others, our approach is simple and effective in feature detection, strength in robustness. Therefore, the video surveillance based on our method is practicable in (but not limited to) many scenarios where the background is known.

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