An Efficient Constrained Learning Algorithm for Stable 2D IIR Filter Factorization

Abstract EN

A constrained neural network optimization algorithm is presented for factorizing simultaneously the numerator and denominator polynomials of the transfer functions of 2-D IIR filters.

The method minimizes a cost function based on the frequency response of the filters, along with simultaneous satisfaction of appropriate constraints, so that factorization is facilitated and the stability of the resulting filter is respected.