Title :
Design of wavelets adapted to signals and application
Author :
Maitrot, Aude ; Lucas, Marie-Françoise ; Doncarli, Christian
Author_Institution :
Inst. de Recherche en Commun. et Cybernetique de Nantes, France
Abstract :
This paper addresses the design of wavelets adapted to the processed signals and the considered application. Our approach consists of parameterizing a mother wavelet, and defining a quality criterion for the optimization of the parameters, according to the context. The first parameterization, leading to orthogonal wavelets, considers the coefficients of the scaling filter as the parameters. A second parameterization, leading to semiorthogonal wavelets, consists of convolving an existing wavelet (or scaling function) by a given sequence. In this paper, we explore these two methods and apply them to the supervised classification of signals made of waveform trains.
Keywords :
adaptive signal processing; convolution; optimisation; parameter estimation; sequences; signal classification; signal resolution; wavelet transforms; adaptive signal processing; convolution; optimization; orthogonal wavelets; parameterizing; quality criterion; scaling filter coefficients; scaling function; semiorthogonal wavelets; sequence; supervised signal classification; waveform trains; Algorithm design and analysis; Constraint optimization; Design optimization; Discrete wavelet transforms; Finite impulse response filter; Multiresolution analysis; Process design; Signal design; Signal processing; Wavelet analysis;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1416084