Robust Probabilistic Online Change Detection Algorithm Based On the Continuous Wavelet Transform
In this article we present a change point detection algorithm based on the continuous wavelet transform. At the beginning of the article we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that we describe a probabilistic algorithm which can be used to find changes using our transformed signal. It is shown that our algorithm works well with the presence of some noise and abnormal random bursts.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057025Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1148
 Popov A., Zhukov M., Computation of continuous wavelet transform of discrete signals with adapted mother functions, Proceedings of the SPIE, vol. 7502, pp. 75021E-75021E-6, 2009.
 Bassville M., Nikiforov I.,Detection of abrupt changes. Theory and application, Pretince-Hall, Englewood Cliffs, New Jersey, 1993.
 Burrus C., Ramesh A., Introduction to wavelets and wavelet transforms: A Primer, Pretince-Hall, New Jersey, 1998.
 Charles K., An introduction to wavelets, Academic Press, New York, 1992.
 Degroot M., Schervish M., Probability and Statistics, Pearson Education, Carnegie-Mellon University, 2011.
 German R., Sintering theory and practice, John Wiley and Sons, New York, 1996.
 Wald A., Sequential Analysis, John Wiley and Sons, New York, 1947.