Estimation the Number of Speakers Based on Adaptive Wavelet Transform by Generalized Eigenvalue Decomposition and K-means Clustering

2019 ◽  
Author(s):  
Ali Dehghan Firoozabadi ◽  
Pablo Irarrazaval ◽  
Pablo Adasme ◽  
Hugo Durney ◽  
Miguel Sanhueza Olave ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Eigenvalue Decomposition ◽  
Adaptive Wavelet ◽  
Generalized Eigenvalue ◽  
Generalized Eigenvalue Decomposition ◽  
Adaptive Wavelet Transform

A novel method for estimating the number of speakers based on generalized eigenvalue–vector decomposition and adaptive wavelet transform by using K-means clustering

2020 ◽  
Vol 14 (5) ◽  
pp. 1017-1025
Author(s):  
Ali Dehghan Firoozabadi ◽  
Pablo Irarrazaval ◽  
Pablo Adasme ◽  
David Zabala-Blanco ◽  
Cesar Azurdia-Meza
Keyword(s):  
Wavelet Transform ◽  
Adaptive Wavelet ◽  
Generalized Eigenvalue ◽  
Vector Decomposition ◽  
Novel Method ◽  
Adaptive Wavelet Transform

Adaptive wavelet transform based on cross-validation method and its application to GPS multipath mitigation

GPS Solutions ◽  
2007 ◽  
Vol 12 (2) ◽  
pp. 109-117 ◽  
Author(s):  
P. Zhong ◽  
X. L. Ding ◽  
D. W. Zheng ◽  
W. Chen ◽  
D. F. Huang
Keyword(s):  
Wavelet Transform ◽  
Cross Validation ◽  
Multipath Mitigation ◽  
Adaptive Wavelet ◽  
Validation Method ◽  
Adaptive Wavelet Transform

scholarly journals Identification and Representation of Multi-Pulse Near-Fault Strong Ground Motion Using Adaptive Wavelet Transform

2019 ◽  
Vol 9 (2) ◽  
pp. 259 ◽  
Author(s):  
Chunxu Xia ◽  
Chunguang Liu
Keyword(s):  
Wavelet Transform ◽  
Pulse Energy ◽  
Horizontal Direction ◽  
Mother Wavelet ◽  
Adaptive Wavelet ◽  
Near Fault ◽  
Seismic Motion ◽  
Adaptive Wavelet Transform ◽  
Mother Wavelets ◽  
Strong Ground

In order to identify the horizontal seismic motion owning the largest pulse energy, and represent the dominant pulse-like component embedded in this seismic motion, we used the adaptive wavelet transform algorithm in this paper. Fifteen candidate mother wavelets were evaluated to select the optimum wavelet based on the similarities between the candidate mother wavelet and the target seismic motion, evaluated by the minimum cross variance. This adaptive choosing algorithm for the optimum mother wavelet was invoked before identifying both the horizontal direction owning the largest pulse energy and every dominant pulse, which provides the optimum mother wavelet for the continuous wavelet transform. Each dominant pulse can be represented by its adaptively selected optimum mother wavelet. The results indicate that the identified multi-pulse component fits well with the seismic motion. In most cases, mother wavelets in one multi-pulse seismic motion were different from each other. For the Chi-Chi event (1999-Sep-20 17:47:16 UTC, Mw = 7.6), 62.26% of the qualified pulse-like earthquake motions lay in the horizontal direction ranging from ±15° to ±75°. The Daubechies 6 (db6) mother wavelet was the most frequently used type for both the first and second pulse components.

scholarly journals Costs and Advantages of Object-Based Image Coding with Shape-Adaptive Wavelet Transform

2007 ◽  
Vol 2007 ◽  
pp. 1-13 ◽  
Author(s):  
Marco Cagnazzo ◽  
Sara Parrilli ◽  
Giovanni Poggi ◽  
Luisa Verdoliva
Keyword(s):  
Wavelet Transform ◽  
Image Coding ◽  
Adaptive Wavelet ◽  
Object Based ◽  
Adaptive Wavelet Transform
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