Abstract
The extraction of Impulse Response Functions (Markov parameters) is a major feature on dynamic systems identification. The convolution integral is a most important input-output relationship for linear systems. Existing methods for calculating the IRFs from the convolution integral are carried out in time or frequency domains. The orthonormal wavelet transform consists on decomposing a given signal on mutually orthogonal local basis functions. It is possible to make use of the orthogonal properties of wavelets for calculating the convolution integral. The wavelet domain preserves the temporal nature of data and, simultaneously, different frequency bands are isolated by the multiresolution analysis, without loosing the orthogonality of the wavelet terms. Algorithm matrices are well conditioned and the method is not very sensitive to output noise. Simulated and experimental analysis are performed and results presented.
