Optimal wavelets for signal decomposition and the existence of scale limited signals
Odegard, Jan E.
Gopinath, Ramesh A.
Burrus, C. Sidney
Wavelet methods give a flexible alternative to Fourier methods in non-stationary signal analysis. The concept of <i>band-limitedness</i> plays a fundamental role in Fourier analysis. Since wavelet theory replaces <i>frequency</i> with <i>scale</i>, a natural question is whether there exists a useful concept of <i>scale-limitedness</i>. Obvious definitions of scale-limitedness are too restrictive, in that there would be few or no useful scale-limited signals. This paper introduces a viable definition for scale-limited signals, and shows that the class is rich enough to include bandlimited signals, and impulse trains, among others. Moreover, for a wide choice of criteria, we show how to design the optimal wavelet for representing a given signal, and how to design <i>robust</i> wavelets that optimally represent certain classes of signals.
Wavelet based Signal/Image Processing; wavelets