Obtaining accurate confidence regions for the estimated zeros andpoles in system identification problems

In this note, a method is proposed to generate improved uncertainty bounds on the poles and zeros of an identified system. The uncertainty ellipsoids are replaced by dedicated uncertainty regions with a given probability level. The method can be applied to Markov estimators in the time or frequency domain     

Design of high-order Chebyshev FIR filters in the complex domainunder magnitude constraints

This article discusses the design of FIR filters that approximate a complex-valued target frequency response in a Chebyshev sense. Additionally, the required stopband attenuation can be specified. Solving the dual of a semi-infinite linear program is currently the most efficient way to design such filters, but numerical problems prevent the design of high-order FIR filters. Modifications are proposed to overcome this limitation. Furthermore, an efficient method is presented for generating starting values that are close to the optimal solution such that the number of iterations is considerably reduced. Examples of filters with a length up to 250 taps are included     

Design of stable IIR filters in the complex domain by automaticdelay selection

A major problem encountered when designing infinite impulse response (IIR) filters in the complex domain is to ensure that the filter is stable. Instability occurs frequently when the IIR filter approximates the inverse of a nonminimum phase system. This is often the case for equalization filters. Addition of delay to the target frequency response can result in a stable filter. However, to date, delay selection has been a matter of trial and error. The article presents an automated method for finding the delay