scholarly journals Highly Nonstationary Wavelet Packets

2002 ◽  
Vol 12 (2) ◽  
pp. 209-229 ◽  
Author(s):  
Morten Nielsen
Keyword(s):  
Wavelet Packets

Multipath extraction and mitigation for static relative positioning based on adaptive layer wavelet packets, bootstrapped searches and CNR constraints

GPS Solutions ◽  
2021 ◽  
Vol 25 (3) ◽  
Author(s):  
Mingkun Su ◽  
Yanxi Yang ◽  
Lei Qiao ◽  
Hao Ma ◽  
WeiJun Feng ◽  
...  
Keyword(s):  
Wavelet Packets ◽  
Relative Positioning

EYE DETECTION USING OPTIMAL WAVELET PACKETS AND RADIAL BASIS FUNCTIONS (RBFs)

1999 ◽  
Vol 13 (07) ◽  
pp. 1009-1025 ◽  
Author(s):  
JEFFREY HUANG ◽  
HARRY WECHSLER
Keyword(s):  
Radial Basis Functions ◽  
Detection Task ◽  
Basis Functions ◽  
Wavelet Packets ◽  
Eye Detection ◽  
Robust Performance ◽  
Image Normalization ◽  
Entropy Minimization ◽  
Novel Approach ◽  
Radial Basis

The eyes are important facial landmarks, both for image normalization due to their relatively constant interocular distance, and for post processing due to the anchoring on model-based schemes. This paper introduces a novel approach for the eye detection task using optimal wavelet packets for eye representation and Radial Basis Functions (RBFs) for subsequent classification ("labeling") of facial areas as eye versus non-eye regions. Entropy minimization is the driving force behind the derivation of optimal wavelet packets. It decreases the degree of data dispersion and it thus facilitates clustering ("prototyping") and capturing the most significant characteristics of the underlying (eye regions) data. Entropy minimization is thus functionally compatible with the first operational stage of the RBF classifier, that of clustering, and this explains the improved RBF performance on eye detection. Our experiments on the eye detection task prove the merit of this approach as they show that eye images compressed using optimal wavelet packets lead to improved and robust performance of the RBF classifier compared to the case where original raw images are used by the RBF classifier.

scholarly journals Classification of Endocardial Electrograms Using Adapted Wavelet Packets and Neural Networks

2001 ◽  
Vol 29 (6) ◽  
pp. 483-492 ◽  
Author(s):  
Daniel Strauss ◽  
Jens Jung ◽  
Andreas Rieder ◽  
Yiannos Manoli
Keyword(s):  
Neural Networks ◽  
Wavelet Packets

WAVELET PACKETS ASSOCIATED WITH NONUNIFORM MULTIRESOLUTION ANALYSIS ON POSITIVE HALF LINE

2013 ◽  
Vol 06 (01) ◽  
pp. 1350007 ◽  
Author(s):  
Vikram Sharma ◽  
P. Manchanda
Keyword(s):  
Multiresolution Analysis ◽  
Wavelet Packets ◽  
Half Line ◽  
State University ◽  
Spectral Pairs ◽  
Funct Anal ◽  
Positive Half

Gabardo and Nashed [Nonuniform multiresolution analysis and spectral pairs, J. Funct. Anal.158 (1998) 209–241] introduced the Nonuniform multiresolution analysis (NUMRA) whose translation set is not a group. Farkov [Orthogonal p-wavelets on ℝ+, in Proc. Int. Conf. Wavelets and Splines (St. Petersburg State University, St. Petersburg, 2005), pp. 4–26] studied multiresolution analysis (MRA) on positive half line and constructed associated wavelets. Meenakshi et al. [Wavelets associated with Nonuniform multiresolution analysis on positive half line, Int. J. Wavelets, Multiresolut. Inf. Process.10(2) (2011) 1250018, 27pp.] studied NUMRA on positive half line and proved the analogue of Cohen's condition for the NUMRA on positive half line. We construct the associated wavelet packets for such an MRA and study its properties.

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