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The Fractional Fourier Transform: with Applications in Optics and Signal Processing

TLDR
The fractional Fourier transform (FFT) as discussed by the authors has been used in a variety of applications, such as matching filtering, detection, and pattern recognition, as well as signal recovery.
Abstract
Preface. Acknowledgments. Introduction. Signals, Systems, and Transformations. Wigner Distributions and Linear Canonical Transforms. The Fractional Fourier Transform. Time-Order and Space-Order Representations. The Discrete Fractional Fourier Transform. Optical Signals and Systems. Phase-Space Optics. The Fractional Fourier Transform in Optics. Applications of the Fractional Fourier Transform to Filtering, Estimation, and Signal Recovery. Applications of the Fractional Fourier Transform to Matched Filtering, Detection, and Pattern Recognition. Bibliography on the Fractional Fourier Transform. Other Cited Works. Credits. Index.

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Citations
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Proceedings ArticleDOI

A Time-Fractional Fourier Joint Representation-Based Parameter Estimation Method for Chirp/Frequency Hopping Spread Spectrum Signal

TL;DR: In this article, a parameter estimation technique based on the short-time fractional Fourier transform (STFRFT) for Chirp /Frequency Hopping (Chirp/FH) spread spectrum signal is proposed.
Journal Article

Image Compression Algorithm Using Two Dimensional Discrete Cosine Transform

TL;DR: In this proposed work the two dimensional discrete cosine transform is used for image compression and the performance of proposed technique over existing technique is superior.
Journal ArticleDOI

Graph Signal Processing: Vertex Multiplication

TL;DR: Graph domain extension of differentiation and graph Fourier transform (GFT) is defined such that it shows Fourier duality that differentiation and CM operations are duals of each other under Fourier transformation (FT).
Proceedings ArticleDOI

Simulating paraxial optical systems using the linear canonical transform: properties, issues and applications

TL;DR: Property of the linear canonical transform are examined analytically, including how the support and bandwidth of the signal are related to transform parameters, a review of sampling issues and some new proposals in this area.
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