Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4977558 | Signal Processing | 2017 | 36 Pages |
Abstract
This article provides an overview of the cubic phase function (CPF) as a tool proposed for both parametric and nonparametric estimation of the frequency modulated (FM) and in particular polynomial phase signals (PPS). This simple tool motivated small revolution in this field with numerous extensions and applications. We are describing the CPF and compare some of its extensions for both one-dimensional and two-dimensional signals. The comparisons are performed in terms of accuracy (measured with signal-to-noise (SNR) threshold and mean-squared error (MSE)) and computational complexity. Also, we review the CPF and related transforms applications.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Igor DjuroviÄ, Marko SimeunoviÄ, Pu Wang,