Abstract

Wavelet transforms as they apply to optimal receiver design are studied. We start with an overview of the Karhunen–Loéve transform and explore the relationship between wavelet bases and the Karhunen–Loéve transform. We show that the dyadic wavelet basic can constitute the eigenfunction basis of a random process. With the help of this foundation, the design of an optimal receiver by the use of a the wavelet expansion is described. The relationship of this receiver to the wavelet-transform-based adaptive filter is also established.

© 1994 Optical Society of America

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