TY - JOUR
T1 - Local eigenfunctions based suboptimal wavelet packet representation of contaminated chaotic signals
AU - Bukkapatnam, Satish T.S.
AU - Kumara, Soundar R.T.
AU - Lakhtakia, Akhlesh
N1 - Funding Information:
The authors thank two referees for helpful remarks that improved the presentation of this work. Satish Bukkapatnam wishes to acknowledge the Zumberge Grant of the University of Southern California as well as support from the Ford Motor Company. Soundar Kumara thanks the US Army Research Of"ce for their support under grant DAA H04-96-1-0082.
PY - 1999/10
Y1 - 1999/10
N2 - We report a suboptimal wavelet packet representation (SWPR) of signals emanating from a chaotic attractor contaminated by low levels of noise. Our method-geared towards choosing a suboptimal scaling function to parsimoniously represent the signal-involves extracting local eigenfunctions using artificial ensembles generated from a pseudo-probability space, and using the extracted local eigenfunctions to develop a suboptimal scaling function. The application of our novel representation method to actual acoustic emission (AE) signals, sampled as time-series data (TSD) from the turning process, reveals the superiority of these methods over the existing signal representations.
AB - We report a suboptimal wavelet packet representation (SWPR) of signals emanating from a chaotic attractor contaminated by low levels of noise. Our method-geared towards choosing a suboptimal scaling function to parsimoniously represent the signal-involves extracting local eigenfunctions using artificial ensembles generated from a pseudo-probability space, and using the extracted local eigenfunctions to develop a suboptimal scaling function. The application of our novel representation method to actual acoustic emission (AE) signals, sampled as time-series data (TSD) from the turning process, reveals the superiority of these methods over the existing signal representations.
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U2 - 10.1093/imamat/63.2.149
DO - 10.1093/imamat/63.2.149
M3 - Article
AN - SCOPUS:0033336973
VL - 63
SP - 149
EP - 162
JO - IMA Journal of Applied Mathematics
JF - IMA Journal of Applied Mathematics
SN - 0272-4960
IS - 2
ER -