Work

Phase Retrieval From Multiple-Window Short-Time Fourier Measurements

Year: 2017

Type: article

Abstract: In this paper, we introduce two undirected graphs depending on supports of signals and windows, and we show that the connectivity of those graphs provides either necessary or sufficient conditions to phase retrieval of a signal from magnitude measurements of its multiple-window short-time Fourier transform. Also, we propose an algebraic reconstruction algorithm, and provide an error estimate to our algorithm when magnitude measurements are corrupted by deterministic/random noises.

Source: IEEE Signal Processing Letters

DOI: 10.1109/lsp.2017.2663668

Authors: Lan Li, Cheng Cheng, Deguang Han, Qiyu Sun, Guangming Shi

Institutions: Xidian University, Xi’an University, University of Central Florida

Language: English

Topic: Mathematical Analysis and Transform Methods

Subfield: Applied Mathematics

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, National Natural Science Foundation of China, Specialized Research Fund for the Doctoral Program of Higher Education of China

Awards: G1193034539, 面向大数据的预期形状导向压缩感知成像的重建方法研究, Frame-Based Kernel Analysis and Algorithms for Fast Recovery of Erasures and Multiplexing, Nonlinear Sampling Theory: Sparsity, Localization and Optimization