The paper presents the development of an algorithm to obtain stable allpass filter, which acts as a group delay equalizer, with the aim to equalize group delay of the polynomial IIR filter in a maximal flat sense. The proposed method relies on a set of nonlinear equations, derived directly from the flatness conditions of the group delay response at the origin in the [Formula: see text]-plane, with the order to obtain the unknown values of the allpass filter coefficients. The algorithm implemented in the MATLAB platform returns the coefficients of allpass filter. In the given example, first we construct a minimum phase polynomial IIR digital filter with a maximally flat magnitude at origin, next we augment the system with cascade connection of nonminimum allpass digital filter with order to equalize the group delay response of the whole filter in a maximally flat sense.
A new class of filter functions with pass-band ripple which derives its origin from a method of determining the chained function lowpass filters described by Guglielmi and Connor is introduced. The closed form expressions of the characteristic functions of these filters are derived by using orthogonal Jacobi polynomial. Since the Jacobi polynomials can not be used directly as filtering function, these polynomials have been adapted by using the parity relation for Jacobi polynomials in order to be used as a filter approximating function. The obtained magnitude response of these filters is more general than the magnitude response of published Chebyshev and Legendre chained function filter, because two additional parameters of modified Jacobi polynomials as two additional degrees of freedom are available. It is shown that proposed modified Jacobi chained function filters approximation also includes the Chebyshev chained function filters, the Legendre chained function filter, and many other types of filter approximations, as its special cases.
A new class of continuous-time low-pass filter using a set of Jacobi polynomials, with all transmission zeros at infinity, is described. The Jacobi polynomial has been adapted by using the parity relation for Jacobi polynomials in order to be used as a filter approximating function. The resulting class of polynomials is referred to as a pseudo Jacobi polynomials, because they are not orthogonal. The obtained magnitude response of these filters is more general than the magnitude response of the classical ultraspherical filter, because of one additional degree of freedom available in pseudo Jacobi polynomials. This additional parameter may be used to obtain a magnitude response having either smaller passband ripples or sharper cutoff slope. Monotonic, critical monotonic, or nearly monotonic passband filter approximating functions can be also generated. It is shown that proposed pseudo Jacobi polynomial filter approximation also includes the Chebyshev filter of the first kind, the Chebyshev filter of the second kind, the Legendre filter, and many transitional filter approximations, as its special cases. Several examples are presented, and detailed formulas including the practical suggestions for their efficient implementation are also provided. The proposed nearly monotonic filter is compared with the least-square-monotonic filters, designed as critical monotonic, in details. The advantages of the new filters are discussed.
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