Frequency-sampling filters: An improved model structure for step-response identification

This paper presents a new methodology for step-response identification using the frequency-sampling filter (FSF) model. The advantages of the FSF model structure over the popular finite-impulse-response (FIR) model are (i) the number of parameters to be estimated is independent of the choice of sampling interval, and is generally far fewer than the number required by the FIR model to obtain an accurate estimate of the step response, and (ii) the general conditioning of the correlation matrix is better with the FSF model because of the reduction in the number of parameters that need to be estimated and to the narrow-bandpass nature of the frequency sampling filters.