Title :
Quasi positive sampling in wavelet subspaces
Author :
Pulido, J. ; Zarowski, C.J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Alberta Univ., Edmonton, Alta., Canada
Abstract :
The wavelet transform is an innovative tool for function approximation and signal compression. It has some advantages in the analysis of signals compared to other orthogonal systems. However, as with other classical orthogonal systems, it presents problems as excessive oscillations in the partial sums and the Gibbs phenomenon can arise S. E. Kelly (1996). In other orthogonal systems this problem is solved using summability methods but these methods cannot be implemented as they are in wavelet expansions. Walter and Shen (1998), propose an alternative method for wavelet systems. However, its practical implementation presents computational problems. This paper considers a modification of Walter and Shen (1998), for approximation of signals hi the interval [0, ∞] where, through the truncation of sums, we obtain a better computational behavior.
Keywords :
data compression; function approximation; sampling methods; signal denoising; wavelet transforms; Gibbs phenomenon; data compression; function approximation; quasi positive sampling; signal compression; signal denoising; statistical analysis; wavelet transform; Convergence; Function approximation; Kernel; Multiresolution analysis; Sampling methods; Signal analysis; Wavelet analysis; Wavelet packets; Wavelet transforms;
Conference_Titel :
Communications, Computers and signal Processing, 2003. PACRIM. 2003 IEEE Pacific Rim Conference on
Print_ISBN :
0-7803-7978-0
DOI :
10.1109/PACRIM.2003.1235846