Coherence Modified for Sensitivity to Relative Phase of Real Band-Limited Time Series

Abstract

As is well known, coherence does not distinguish the relative phase of a pair of real, sinusoidal time series; the coherence between them is always unity. This behavior can limit the applicability of coherence analysis in the special case where the time series are band-limited (nearly-monoch- romatic) and where sensitivity to phase differences is advantageous. We propose a simple mod-ification to the usual formula for coherence in which the cross-spectrum is replaced by its real part. The resulting quantity behaves similarly to coherence, except that it is sensitive to relative phase when the signals being compared are strongly band-limited. Furthermore, it has a useful interpretation in terms of the zero-lag cross-correlation of real band-passed versions of the time series.

Share and Cite:

Menke, W. (2014) Coherence Modified for Sensitivity to Relative Phase of Real Band-Limited Time Series. Applied Mathematics, 5, 2739-2745. doi: 10.4236/am.2014.517261.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Olsen, P.E. and Kent, D.V. (1996) Milankovitch Climate Forcing in the Tropics of Pangea during the Late Triassic. Paleooceanography, Paleoclimatology, Paleoecology, 122, 1-26.
http://dx.doi.org/10.1016/0031-0182(95)00171-9
[2] Bendat, J.S. and Piersol, A.G. (2010) Random Data, Anaysis and Measurement Procedures. John Wiley and Sons, New York.
http://dx.doi.org/10.1002/9781118032428
[3] Sandberg, J. and Hansson, M. (2006) Cohernece Estimation between EEG Signals Using Multiple Window Time-Frequency Analysis Compared to Gaussian Kernels. Proceedings of the 14th European Signal Processing Conference, Florence, 4-8 September 2006.
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2006/papers/1568981924.pdf
[4] Lawson, C.L. and Hanson, R.J. (1974) Solving Least Squares Problems. Prentice-Hall, New York.
[5] Millar, R.B. (2011) Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB. John Wiley and Sons, New York.
http://dx.doi.org/10.1002/9780470094846
[6] Menke, W. (2012) Geophysical Data Analysis: Discrete Inverse Theory. MATLAB Edition, Elsevier, Amsterdam.
[7] Bracewell, R.N. (2000) The Fourier Transform and Its Applications. 3rd Edition, McGraw-Hill, New York.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.