A new approach for selecting the number of the eigenvalues in singular spectrum analysis. Issue 1 (January 2016)

• Record Type: Journal Article
• Authors: Alharbi, Nader; Hassani, Hossein
• Is Part Of: Journal of the Franklin Institute. Volume 353:Issue 1(2016:Jan.)
• Page Start: 1
• Page End: 16
• Publication Date: 2016-01
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2015.10.015
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: Singular spectrum analysis (SSA) is a reliable technique for separating an arbitrary signal from a noisy time series (signal+noise). The SSA technique is based upon two main selections: window length, L, and the number of the eigenvalues, r . These values play an important role for the reconstruction stage. In this paper, we introduce a new approach for selecting the optimal value of r, which is based on the distribution of the eigenvalues of a scaled Hankel matrix. The proposed approach is applied to a number of simulated and real data with different structures. The results indicate that the proposed approach has potential in selecting the value of r for signal extraction.