RESEARCH OF CHANGES OF ENTROPY AND ENERGY ON SIGNAL DECOMPOSITION
DOI:
https://doi.org/10.15588/1607-3274-2013-2-9Keywords:
wavelet transformation, signal delineation, optimal signal decomposition.Abstract
Research of changes of entropy and energy on signal decomposition is presented. Coifman’s method for the purpose for signal delineation was modified. The method of complex signal delineation based on wavelet transformation and information theory is proposed. The algorithm for the signal components separation is developed. The proposed method based on research of total entropy of both signal formed components. The first component is the reconstructed source signal after wavelet transformation on the current decomposition level in which the approximation coefficients must be equals to zero. The second component is the residue from the deduction of the source signal and the second component on the current decomposition level. The turning point of the total entropy curve denotes the most unstable system state in which the components can be identified. The most unstable system state is system state having zero increment of information. Entropy increments until the turning point and it decrease after. The sum of the sinusoids was used as test signal. The results of the method have high accuracy.References
Sen, M. Real-time digital signal processing. Implementations and applications / M. Sen. – Wiley, 2006. – 667 p.
Misiti, M. Wavelet and their applications / M. Misiti, G. Oppenheim. – USA : ISTE, 2007. – 330 p.
Percival, D. Wavelet methods for time series analysis / D. Percival, A. Walden. – Cambridge university press, 2003. – 566 p.
Mallat, S. A wavelet tour of signal processing / S. Mallat. – USA: Academic Press, 1998 – 805 p.
Coifman, R. R. Entropy-based algorithms for best basis selection / R. R. Coifman, M. V. Wickerhauser // IEEE Trans. on Inf. Theory. – 1992. – Vol. 38 (2). – P. 713–718.
Martin, N. Mathematical theory of entropy / N. Martin. – Cambridge university press, 1984. – 258 p.
Muller, I. Entropy and energy / I. Muller, W. Weiss. – Springer Press, 2005. – 273 p.
Fang, S. Entropy optimization and mathematical programming / S. Fang, J. Rajasekera. – USA: Kluwer academic publishers, 1997. – 273 p.
Shannon, K. A Mathematical theory of communication /K. Shannon // The Bell System Technical Journal. – 1948. – Vol. 27. – P. 379–423.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2014 V. I. Dubrovin, J. V. Tverdohleb
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Creative Commons Licensing Notifications in the Copyright Notices
The journal allows the authors to hold the copyright without restrictions and to retain publishing rights without restrictions.
The journal allows readers to read, download, copy, distribute, print, search, or link to the full texts of its articles.
The journal allows to reuse and remixing of its content, in accordance with a Creative Commons license СС BY -SA.
Authors who publish with this journal agree to the following terms:
-
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License CC BY-SA that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
-
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
-
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.