Sampling and Reconstruction in Arbitrary Measurement and Approximation Spaces Associated With Linear Canonical Transform

• Published in: IEEE transactions on signal processing Vol. 64; no. 24; pp. 6379 - 6391
• Main Authors: Shi, Jun, Liu, Xiaoping, He, Lei, Han, Mo, Li, Qingzhong, Zhang, Naitong
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.12.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Approximation error; Filtering theory; Frequencies; function spaces; Interpolation; Kernel; Linear canonical transform; oblique projection; Optics; Riesz basis; sampling and approximation; Signal processing; Transforms
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2016.2602808

The linear canonical transform (LCT), which generalizes many classical transforms, has been shown to be a powerful tool for signal processing and optics. Sampling theory of the LCT for bandlimited signals has blossomed in recent years. However, in practice signals are never perfectly bandlimited, and in many cases measurement devices are nonideal. The objective of this paper is to develop a sampling theorem for the LCT from general measurements, which can provide a suitable and realistic model of sampling and approximation for real-world applications. We first describe a general class of approximation spaces for the LCT and provide a full characterization of their basis functions. Then, we propose a generalized sampling theorem for arbitrary measurement and approximation spaces associated with the LCT. Several properties of the proposed sampling theorem are also discussed. Furthermore, the approximation error is estimated. Finally, numerical results and several applications of the derived results are presented.