2020Unpublished venueRequires access

Design of Complex IIR Digital Filters using Transformed Variables

Kenneth W. Martin

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Abstract

The design of real IIR digital filters using conformal transform variables has been extensively researched; this paper deals with the design of complex IIR digital filters having non-symmetric transfer functions, and directly designed using transformed variables. The transformation used is an extension of a transform used previously for continuous-time complex filters; the extension adds a bilinear function which enables the transform to be used for designing discrete-time transfer functions. Approximations having equiripple and monotonically decreasing passbands are supported. Methods for improving numerical accuracy and minimizing coefficient sensitivities are described. A high-order cascade filter example simulated using Monte Carlo analysis demonstrates almost ideal accuracy.

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What this paper is about

The design of real IIR digital filters using conformal transform variables has been extensively researched; this paper deals with the design of complex IIR digital filters having non-symmetric transfer functions, and directly designed using transformed variables. The transformation used is an extension of a transform used previously for continuous-time complex filters; the extension adds a bilinear function which enables the transform to be used for designing discrete-time transfer functions. Approximations having equiripple and monotonically decreasing passbands are supported. Methods for improving numerical accuracy and minimizing coefficient sensitivities are described. A high-order cascade filter example simulated using Monte Carlo analysis demonstrates almost ideal accuracy.

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Available abstract

The design of real IIR digital filters using conformal transform variables has been extensively researched; this paper deals with the design of complex IIR digital filters having non-symmetric transfer functions, and directly designed using transformed variables. The transformation used is an extension of a transform used previously for continuous-time complex filters; the extension adds a bilinear function which enables the transform to be used for designing discrete-time transfer functions. Approximations having equiripple and monotonically decreasing passbands are supported. Methods for improving numerical accuracy and minimizing coefficient sensitivities are described. A high-order cascade filter example simulated using Monte Carlo analysis demonstrates almost ideal accuracy.

Key concepts: Bilinear transform, Infinite impulse response, 2D Filters, Transfer function, Digital filter, Network synthesis filters, Transformation (genetics), Algorithm

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