Dynamic Time-frequency Feature Extraction for Brain Activity Recognition

2018 ◽  
Author(s):  
Yang Shi ◽  
Fangyu Li ◽  
Tianming Liu ◽  
Fred R. Beyette ◽  
WenZhan Song
Keyword(s):  
Feature Extraction ◽  
Activity Recognition ◽  
Brain Activity ◽  
Time Frequency ◽  
Dynamic Time ◽  
Frequency Feature

Research on a feature extraction method for local faults in planetary gearboxes based on improved dynamic time warping

2021 ◽  
Vol 63 (8) ◽  
pp. 465-471
Author(s):  
Shang Zhiwu ◽  
Yu Yan ◽  
Geng Rui ◽  
Gao Maosheng ◽  
Li Wanxiang
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Frequency Domain ◽  
Extraction Method ◽  
Dynamic Time Warping ◽  
Spectral Feature ◽  
Time Warping ◽  
Feature Extraction Method ◽  
Time Frequency ◽  
Dynamic Time

Aiming at the local fault diagnosis of planetary gearbox gears, a feature extraction method based on improved dynamic time warping (IDTW) is proposed. As a calibration matching algorithm, the dynamic time warping method can detect the differences between a set of time-domain signals. This paper applies the method to fault diagnosis. The method is simpler and more intuitive than feature extraction methods in the frequency domain and the time-frequency domain, avoiding their limitations and disadvantages. Due to the shortcomings of complex calculation, singularity and poor robustness, the paper proposes an improved method. Finally, the method is verified by envelope spectral feature analysis and the local fault diagnosis of gears is realised.

Time-frequency feature extraction from frequency-modulated sounds in a population of auditory cortical neurons

2008 ◽  
Vol 29 (1) ◽  
pp. 36-40 ◽  
Author(s):  
Shunji Sugimoto ◽  
Yuta Suzuki ◽  
Hiroyuki Tanaka ◽  
Michinori Kubota ◽  
Junsei Horikawa
Keyword(s):  
Feature Extraction ◽  
Cortical Neurons ◽  
Time Frequency ◽  
Frequency Feature
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