IIR digital filter design with new stability constraint based on argument principle
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Minimax design of IIR digital filters using iterative SOCP
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Design methodology for nearly linear-phase recursive digital filters by constrained optimization
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Minimax design of IIR digital filters using SDP relaxation technique
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Digital IIR filter design using multi-objective optimization evolutionary algorithm
Applied Soft Computing
Two-stage ensemble memetic algorithm: Function optimization and digital IIR filter design
Information Sciences: an International Journal
Fixed-point digital IIR filter design using two-stage ensemble evolutionary algorithm
Applied Soft Computing
Filter-based fading channel modeling
Modelling and Simulation in Engineering - Special issue on Modeling and Simulation of Mobile Radio Channels
Hi-index | 35.68 |
The problem of designing optimal digital IIR filters with frequency responses approximating arbitrarily chosen complex functions is considered. The real-valued coefficients of the filter's transfer function are obtained by numerical minimization of carefully formulated cost, which is referred here to as the weighted integral of the squared error (WISE) criterion. The WISE criterion linearly combines the WLS criterion that is used in the weighted least squares approach toward filter design and some time-domain components. The WLS part of WISE enforces the quality of the frequency response of the designed filter, while the time-domain part of the WISE criterion restricts the positions of the filter's poles to the interior of an origin-centred circle with arbitrary radius. This allows one not only to achieve stability of the filter but also to maintain some safety margins. A great advantage of the proposed approach is that it does not impose any constraints on the optimization problem and the optimal filter can be sought using off-the-shelf optimization procedures. The power of the proposed approach is illustrated with filter design examples that compare favorably with results published in research literature