Signal approximation using the bilinear transform

This paper explores the approximation properties of a unique basis expansion, which realizes a bilinear frequency warping between a continuous-time signal and its discrete-time representation. We investigate the role that certain parameters and signal characteristics have on these approximations, an...

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Bibliographic Details
Main Authors: Venkataraman, A., Oppenheim, A.V.
Format: Conference Proceeding
Language:English
Subjects:
Approximation Methods
Bilinear Transformations
Digital signal processing
Discrete transforms
Frequency
Laplace equations
Nonlinear distortion
Polynomials
Sampling methods
Signal analysis
Signal Detection
Signal processing
Signal representations
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Description
Summary:This paper explores the approximation properties of a unique basis expansion, which realizes a bilinear frequency warping between a continuous-time signal and its discrete-time representation. We investigate the role that certain parameters and signal characteristics have on these approximations, and we extend the analysis to a windowed representation, which increases the overall time resolution. Approximations derived from the bilinear representation and from Nyquist sampling are compared in the context of a binary detection problem. Simulation results indicate that, for many types of signals, the bilinear approximations achieve a better detection performance.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2008.4518463