Multidimensional Systems and Signal Processing
Equalization of loudspeaker and room responses using Kautz filters: direct least squares design
EURASIP Journal on Applied Signal Processing
Combining evolutionary and stochastic gradient techniques for system identification
Journal of Computational and Applied Mathematics
FIR, allpass, and IIR variable fractional delay digital filter design
IEEE Transactions on Circuits and Systems Part I: Regular Papers
IIR digital filter design with new stability constraint based on argument principle
IEEE Transactions on Circuits and Systems Part I: Regular Papers
IEEE Transactions on Circuits and Systems Part I: Regular Papers
A novel approach to stable iir digital filter design
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Re-estimation of linear predictive parameters in sparse linear prediction
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Minimax design of IIR digital filters using SDP relaxation technique
IEEE Transactions on Circuits and Systems Part I: Regular Papers
VISA: versatile impulse structure approximation for time-domain linear macromodeling
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
Journal of Signal Processing Systems
| Hi-index | 35.68 |
An algorithm is presented for the least-squares approximation of FIR filters by IIR filters. The algorithm is an iterative procedure where each iteration requires the solution of an overdetermined set of linear equations and some digital filtering operations. All calculations are performed with the numerator and denominator coefficients of the transfer functions. A conversion to state-space descriptions is not necessary. Examples show that the approximation error is as small as that of the IIR filters obtained with balanced model reduction. Moreover, the effects of numerical errors are negligible. Thus, our algorithm is applicable even in cases where the FIR filter length is large