[1] T. Alexandrov, S. Bianconcini, E. B. Dagum, P. Maass and T. McElroy, A review of some
modern approaches to the problem of trend extraction, In Research Report Series, Statistics
2008-3, U.S. Census Bureau, Washington, 2009.
[2] S. Cleveland and S. Devlin, Locally-weighted regression: an approach to regression analysis
by local fitting, J. Am. Stat., Assoc. 83 (1988), 596{610.
[3] N. Golyandina and A. Zhigljavsky, Singular spectrum analysis for time series, Briefs in
Statistics, Springer, Berlin, 2013.
[4] M. Holcapek and L. Nguyen, Suppression of high frequencies in time series using fuzzy trans-
form of higher degree, Information Processing and Management of Uncertainty in Knowledge-
Based Systems: 16th International Conference, IPMU 2016, Eindhoven, The Netherlands,
Springer, (2016), 705{716.
[5] M. Holcapek, V. Novak and I. Perfilieva, Noise reduction in time series using F-transform,
In: Proc. IEEE International Conference on Fuzzy Systems, Hyderabad, (2013), 1{8.
[6] M. Holcapek, I. Perfilieva, V. Novak and V. Kreinovich, Necessary and sufficient conditions
for generalized uniform fuzzy partitions, Fuzzy Sets and Systems, 277 (2015), 97{121.
[7] M. Holcapek and T. Tichy, A smoothing filter based on fuzzy transform, Fuzzy Sets and
Systems, 180 (1) (2011), 69{97.
[8] A. H. Jazwinski, Stochastic Processes and Filtering Theory, Mineola, NY: Dover Publica-
tions, 2007.
[9] I. Kodorane and S. Asmuss, On approximation properties of spline based F-transform with
respect to fuzzy m-partition, in: G. Pasi, J. Montero, D. Ciucci (eds.), Proc. of the 8th
conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13), Atlantis
Press, (2013), 772{779.
[10] M. Kokainis and S. Asmuss, Approximation properties of higher degree F-transforms based
on B-splines, In: Proc. IEEE International Conference on Fuzzy Systems, Istanbul, (2015),
1{8.
[11] L. Nguyen and V. Novak, Filtering out high frequencies in time series using F-transform with
respect to raised cosine generalized uniform fuzzy, In: Proc. IEEE International Conference
on Fuzzy Systems, Istanbul, (2015), 1{8.
[12] V. Novak, I. Perfilieva, M. Holcapek and V. Kreinovich, Filtering out high frequencies using
F{transform, Information Sciences, 274 (2014), 192{209.
[13] V. Novak, M. Stepnicka, A. Dvorak, I. Perfilieva, V. Pavliska and L. Vavrckova, Analysis of
seasonal time series using fuzzy approach, Int. J. Gen. Syst., 39 (2010), 305{328.
[14] V. Novak, M. Stepnicka, I. Perfilieva and V. Pavliska, Analysis of periodical time series
using soft computing methods, In: D. Ruan, J. Montero, J. Lu, L. Martinez, P. D'hondt, E.
E. Kerre (eds.), Computational Intelligence in Decision and Control, World Scientific, New
Jersey, (2008), 55{60.
[15] I. Perfilieva, Fuzzy transforms, Peters, James F. (ed.) et al., Transactions on Rough Sets
II. Rough sets and fuzzy sets. Berlin: Springer. Lecture Notes in Computer Science 3135.
Journal Subline, (2004), 63{81.
[16] I. Perfilieva, Fuzzy transforms: Theory and applications, Fuzzy Sets and Systems, 157(8)
(2006), 993{1023.
[17] I. Perfilieva and M. Dankova, Towards F-transform of a higher degree, in: In Proc. of
IFSA/EUSFLAT 2009, Lisbon, Portugal, (2009), 585{588.
[18] I. Perfilieva, M. Dankova and B. Bede, Towards a higher degree F-transform, Fuzzy Sets and
Systems, 180 (1) (2011), 3{19.
[19] I. Perfilieva and R. Valasek, Fuzzy transforms in removing noise, Innovations in Hybrid
Intelligent Systems, Springer Berlin/Heidelberg, (2005), 221{230.
[20] E. Titchmarsh, Introduction to the Theory of Fourier Integrals, Oxford University Press,
Oxford, 1948.
[21] A. M. Yaglom, An introduction to the Theory of Stationary Random Functions, Revised
English ed. Translated and edited by Richard A. Silverman, Englewood Clis, NJ: Prentice-
Hall, Inc. XIII, 1962.