Design of Stable Circularly Symmetric Two-Dimensional GIC Digital Filters Using PLSI Polynomials

Stabilization of 2D NSHP Recursive Digital Filters with Guaranteed Stability Using PLSI Polynomials

Two-dimensional digital filters have gained wide acceptance in recent years. For recursive filters, nonsymmetric half-plane versions (also known as semicausal) are more general than quarter-plane versions (also known as causal) in approximating arbitrary magnitude characteristics. The major problem in designing two-dimensional recursive filters is to guarantee their stability with the expected ...

The PLSI Method of Stabilizing Two-Dimensional (2-D) Nonsymmetric Half-Plane (NSHP) Recursive Digital Filters

Two-dimensional (2D) recursive digital filters find applications in image processing as inmedical X-ray processing. Nonsymmetric half-plane (NSHP) filters have definitely positive magnitude characteristics as opposed to quarter-plane (QP) filters. In this paper, we provide methods for stabilizing the given 2D NSHP polynomial by the planar least squares inverse (PLSI) method. We have proved in t...

An Overview of Modified Shanks’ Conjecture and Comments on its Validity

This study reports the validity of the modified Shanks’ conjecture on the planar least squares inverse (PLSI) method of stabilizing two-dimensional (2-D) recursive digital filters. A theoretical procedure proposed based on the Lagrange multiplier method of mathematical optimization. The results indicate that the modified Shanks’ conjecture reported by Jury was valid for special classes of 2-D p...

Design of Circularly Symmetric Two-Dimensional Linear-Phase Lowpass FIR Filters using Closed-Form Expressions

The PLSI Method of Stabilizing Two-Dimensional Nonsymmetric Half-Plane Recursive Digital Filters

It should be noted that in (23) and all equations in the rest of the paper that contain the term b′ 00, this term is the constant term of the polynomial B′(z1, z2), which is the stable version of the 2D PLSI polynomial B(z1, z2). Since we have assumed that bi j ’s are the coefficients of the 2D PLSI polynomial, the coefficients of the polynomial B′(z1, z2) are b′ i j ’s. Equation (46) in page n...