Constrained pole-zero filters as discrete-time operators for system approximation

Discrete-time models whether linear or nonlinear, often implicitly use the shift operator to obtain input regression vectors. It has been shown previously that the significantly better performance can be obtained in terms of coefficient sensitivity and output error by using alternative operators to the usual shift operator. These include the delta and gamma operators. In this paper the authors introduce second order pole-zero operators which have more general modelling properties than those previously considered. The authors provide some observations on the behaviour of the operators, considering representational issues and convergence characteristics in particular.

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