Signal Detection

  • James B. Elsner
  • Anastasios A. Tsonis


One of the goals of SSA in time-series analysis is to identify a signal or signals in an observed record against a background of noise (e.g., Rasmusson et al., 1990; Plaut et al., 1995). If we are lacking reasons to anticipate a particular regularity based on physical theory, then we need to decide at what confidence level we can reject the notion that features identified in the record have occurred by chance. As suggested by Allen (1992) we can think of “occurring by chance” to mean “attributable to the stochastic component of the record.” So it is necessary to calculate the probability of these stochastic features exceeding certain levels. It is then possible to estimate the chance of a given feature being the product of random fluctuations or the product of some physical phenomenon.


Monte Carlo Signal Detection Noise Process Monte Carlo Approach Singular Spectrum Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • James B. Elsner
    • 1
  • Anastasios A. Tsonis
    • 2
  1. 1.Florida State UniversityTallahasseeUSA
  2. 2.University of Wisconsin-MilwaukeeMilwaukeeUSA

Personalised recommendations