Detection of unknown signals in arbitrary noise

Authors

Glenn Ierley, Michigan Technological UniversityFollow
Alexander Kostinski, Michigan Technological UniversityFollow

Document Type

Article

Publication Date

9-29-2020

Department

Department of Mathematical Sciences; Department of Physics

Abstract

We devise a simple method for detecting signals of unknown form buried in any noise, including heavy tailed. The method centers on signal-noise decomposition in rank and time: Only stationary white noise generates data with a jointly uniform rank-time probability distribution, U(1,N)×U(1,N), for N data points in a time series. Signals of any kind distort this uniformity. Such distortions are captured by rank-time cumulative distributions permitting all-purpose efficient detection, even for single time series and noise of infinite variance.

Publisher's Statement

© 2020 American Physical Society. Publisher’s version of record: https://doi.org/10.1103/PhysRevE.102.032221

Publication Title

Physical Review E

Recommended Citation

Ierley, G., & Kostinski, A. (2020). Detection of unknown signals in arbitrary noise. Physical Review E, 102(3). http://doi.org/10.1103/PhysRevE.102.032221
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/14313