Abstract
The paper presents two algorithms median smoothing time series. These algorithms are finite procedures. The number of steps of the algorithms defined volume time series. Use these algorithms do not require computation and presents the trend using local medians. An important moment in behalf of the offered algorithms of median filtration is that it is not used the subjective factor, for example, a choice of the window size, quantities of iterations or any other parameters. The procedure of median filtration is connected only with concrete quantity of levels of a time series, and paired or unpaired of their quantity has no basic value.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kendall, M.G.: Design and analysis, and time-series. In: Kendall, M.G., Stuart, A. (eds.) The Advanced Theory Of Statistics, in Three Volumes, vol. 3, 4th edn. Oxford University Press, London (1987)
Pollard, J.H.: A handbook of numerical and statistical techniques. In: Pollard, J.H., vol. 1, Aufl., XVI, 349 S. Cambridge University Press, Cambridge (1977)
Brown, R.G.: Exponential smoothing for predicting demand. https://industrydocuments.library.ucsf.edu/tobacco/docs/jzlc0130. Accessed 11 Oct 2015
Brown, R.G.: Smoothing forecasting and prediction of discrete time series. In: Brown, R.G. p. cm. Reprint. Englewood Cliffs, NJ (1963)
Tukey, W.J.: Exploratory data analysis, In: Tukey, W.J. (ed.) p. 688. Addison-Wesley, Reading (1977)
Huang, T.S.: Two-dimensional digital signal processing II: transforms and median filters. In: Huang, T.S., Justusson, B.I., Nussbaum, H.J., Tyan, S.G., Zohar, S., (eds.) vol. XI, p. 224. Springer, Berlin (1981)
Stork, M.: Median filters theory and applications. In: Stork, M. (ed.). http://www.emo.org.tr/ekler/2130c418d4f02c7_ek.pdf. Accessed 22 June 2015
Arias-Castro, E.: Does median filtering truly preserve edges better than linear filtering? Ann. Stat. 37(3), 1172–2009 (2009)
Fried, R.: On the robust detection of edges in time series filtering. Comput. Stat. Data Anal. 52(2), 1063–1074 (2007)
Kenneth, E.B.: Order statistic filtering and smoothing of time series, Part II. In: Barner, K.E., Arce, G.R. (eds.) Handbook of Statistics, vol. 17, pp. 555–602 (1998)
Liu, S.: Combining pseudo-median filter and median filter to improve performance. In: Liu, S., Chen, L., Fan, X., Qu, Z., Yang, X. (eds.). http://www.meeting.edu.cn/meeting/UploadPapers/1281582612718.pdf. Accessed 22 June 2015
Lukin, V.V.: Adaptive dct-based 1-d filtering of poisson and mixed poisson and impulsive noise. In: Lukin, V.V., Fevralev, D.V., Abramov, S.K., Peltonen, S., Astola, J. (eds.). http://www.eurasip.org/Proceedings/Ext/NLA2008/papers/cr1002.pdf. Accessed 22 June 2015
Yin, L.: Weighted median filters: a tutorial. In: Yin, L., Yang, R., Gabbouj, M., Neuvo, Y. (eds.) IEEE Transactions on Circuits and Systems-11: Analog and Digital Signal Processing, vol. 43, pp. 157–192 (1996)
Liu, Y.: A 1-D time-varying median filter for seismic random, spike-like noise elimination. Geophysics 74(1), V17–V24 (2009)
Chilingarian, A.: Median filtering algorithms for multichannel detectors. In: Chilingarian, A., Hovhannisyan, A., Mailyan, B (eds.). In Proceedings of the 31st icrc, Lodz 1. http://icrc2009.uni.lodz.pl/proc/html/
Pęksiński, J.: Estimation of the variance of the random component in the time series with digital smoothing. Logistyka 3, 5047–5052 (2014)
Kemal, O.: Design and implementation of a single-chip 1-d median filter. Trans. Acoust. Speech Signal Process. 31(5), 1164–1168 (1983)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Dmitriv, H., Kaminsky, R. (2017). Two Algorithms Median Filtering to Identify the Time Series Trend. In: Shakhovska, N. (eds) Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing, vol 512. Springer, Cham. https://doi.org/10.1007/978-3-319-45991-2_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-45991-2_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45990-5
Online ISBN: 978-3-319-45991-2
eBook Packages: EngineeringEngineering (R0)