Processing input data in multimodal applications

Main Article Content

A.H. Kyselova
G.D. Kiselov
A.A. Serhyeyev
A.V. Shalaginov

Abstract

The analysis of methods of smoothing of time series in multimodal applications and estimated parameters of smoothing and a resources consumption of algorithms described in the article

Article Details

How to Cite
Kyselova, A. ., Kiselov, G. ., Serhyeyev, A. ., & Shalaginov, . A. . (2011). Processing input data in multimodal applications. Electronics and Communications, 16(2), 86–92. https://doi.org/10.20535/2312-1807.2011.16.2.268253
Section
Methods and means of processing signals and images

References

J. Jacko and A. Sears, Multimodal Interfaces, The Human-Computer Interaction Handbook: Fundamentals,Evolving Technologies and EmergingApplications, Lawrence Erlbaum Assoc, 2003.

M. Kendall, A. Stuart, and J. K. Ord, Kendall’s advanced theory of statistics, vol. 3. London: Hodder Arnold, 1983.

Y. Lukashin, Adaptive methods for short-term forecasting of time series, M.: Finance and statistics, 2003, p. 415.

E. S. Gardner and D. G. Dannenbring, “FORECASTING WITH EXPONENTIAL SMOOTHING: SOME GUIDELINES FOR MODEL SELECTION”, Decision Sciences, vol. 11, no. 2, pp. 370–383, Apr. 1980. DOI:10.1111/j.1540-5915.1980.tb01145.x

B. Bowerman, J. Bruce, and R. T. O’Connell, Forecasting and Time Series: An Applied Approach Duxbury Thomson Learning, South-Western College Pub; 3rd edition, 1993, p. 848.

M. Zgurovsky and V. Podladchikov, Analytical MethodsKalman filtering for systems witha priori uncertainty, K.: Naukovadumka, 1995, p. 283.