Please use this identifier to cite or link to this item:
Title: Performing fractional delay via fractional singular spectrum analysis
Authors: Zhou, Y
Ling, BWK
Huang, Z 
Chan, YL 
Lin, Y
Issue Date: 2021
Source: Signal, image and video processing, Online first,
Abstract: This paper proposes a fractional singular spectrum analysis (SSA)-based method for performing the fractional delay. First, the input sequence is divided into two overlapping sequences with the first sequence being the input sequence without its last point and the second sequence being the input sequence without its first point. Then, the singular value decompositions (SVD) are performed on the trajectory matrices constructed based on these two sequences. Next, the designs of both the right unitary matrix and the left unitary matrix for generating the new trajectory matrix are formulated as the quadratically constrained quadratic programing problems. The analytical solutions of these quadratically constrained quadratic programing problems are derived via the SVD approach. Finally, the fractional SSA components are obtained by performing the diagonal averaging operation, and the fractional delay sequence is obtained by summing up all the fractional SSA components together. Since the fractional SSA operations are nonlinear and adaptive, our proposed method is a kind of nonlinear and adaptive approach for performing the fractional delay. Besides, by discarding some fractional SSA components, the joint fractional delay operation and the denoising operation can be performed simultaneously.
Keywords: Fractional delay
Fractional singular spectrum analysis
Quadratically constrained quadratic programing
Publisher: Springer
Journal: Signal, image and video processing 
ISSN: 1863-1703
DOI: 10.1007/s11760-021-01954-x
Appears in Collections:Journal/Magazine Article

Open Access Information
Status embargoed access
Embargo End Date 2022-06-16
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

Citations as of May 15, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.