Classification of Alertness and Drowsiness States Using the Complex Wavelet Transform-Based Approach for EEG Records

2021 ◽  
pp. 1-15
Author(s):  
Sachin Taran ◽  
Ravi ◽  
Smith K. Khare ◽  
Varun Bajaj ◽  
G. R. Sinha
Keyword(s):  
Wavelet Transform ◽  
Complex Wavelet Transform ◽  
Complex Wavelet

scholarly journals Dual tree complex wavelet transform-based signal denoising method exploiting neighbourhood dependencies and goodness-of-fit test

2018 ◽  
Vol 5 (9) ◽  
pp. 180436 ◽  
Author(s):  
Khuram Naveed ◽  
Bisma Shaukat ◽  
Naveed ur Rehman
Keyword(s):  
Wavelet Transform ◽  
Goodness Of Fit ◽  
Signal Denoising ◽  
Discrete Wavelet ◽  
Translation Invariance ◽  
Complex Wavelet Transform ◽  
Goodness Of Fit Test ◽  
Denoising Method ◽  
Complex Wavelet

A novel signal denoising method is proposed whereby goodness-of-fit (GOF) test in combination with a majority classifications-based neighbourhood filtering is employed on complex wavelet coefficients obtained by applying dual tree complex wavelet transform (DT-CWT) on a noisy signal. The DT-CWT has proven to be a better tool for signal denoising as compared to the conventional discrete wavelet transform (DWT) owing to its approximate translation invariance. The proposed framework exploits statistical neighbourhood dependencies by performing the GOF test locally on the DT-CWT coefficients for their preliminary classification/detection as signal or noise. Next, a deterministic neighbourhood filtering approach based on majority noise classifications is employed to detect false classification of signal coefficients as noise (via the GOF test) which are subsequently restored. The proposed method shows competitive performance against the state of the art in signal denoising.

scholarly journals DUAL-TREE COMPLEX WAVELET TRANSFORM IN THE FREQUENCY DOMAIN AND AN APPLICATION TO SIGNAL CLASSIFICATION

2005 ◽  
Vol 03 (01) ◽  
pp. 43-65 ◽  
Author(s):  
JULIA NEUMANN ◽  
GABRIELE STEIDL
Keyword(s):  
Wavelet Transform ◽  
Frequency Domain ◽  
Filter Bank ◽  
Filter Design ◽  
Signal Classification ◽  
Complex Wavelet Transform ◽  
Numerical Examples ◽  
Wavelet Filters ◽  
Complex Wavelet

We examine Kingsbury's dual-tree complex wavelet transform in the frequency domain where it can be formulated for standard wavelet filters without special filter design. We prove that the dual-tree filter bank construction leads to wavelets with vanishing negative frequency parts, present numerical examples illustrating the improvement of translation and rotation invariance for various standard wavelet filters and apply the method to the classification of signals.

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