Adaptation in Stochastic Dynamic Systems—Survey and New Results IV: Seeking Minimum of API  in Parameters of Data

Innokentiy V. Semushin; Julia V. Tsyganova

doi:10.4236/ijcns.2013.612055

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Adaptation in Stochastic Dynamic Systems—Survey and New Results IV: Seeking Minimum of API in Parameters of Data ()

Innokentiy V. Semushin, Julia V. Tsyganova

School of Mathematics and Information Technology, Ulyanovsk State University, Ulyanovsk, Russia.

DOI: 10.4236/ijcns.2013.612055 PDF HTML XML 2,816 Downloads 3,888 Views Citations

Abstract

This paper investigates the problem of seeking minimum of API (Auxiliary Performance Index) in parameters of Data Model instead of parameters of Adaptive Filter in order to avoid the phenomenon of over parameterization. This problem was stated by Semushin in [2]. The solution to the problem can be considered as the development of API approach to parameter identification in stochastic dynamic systems.

Keywords

Linear Stochastic Systems; Parameter Estimation; Model Identification; Identification for Control; Adaptive Control MSC (2010); 93E10; 93E12; 93E35

Share and Cite:

I. Semushin and J. Tsyganova, "Adaptation in Stochastic Dynamic Systems—Survey and New Results IV: Seeking Minimum of API in Parameters of Data," International Journal of Communications, Network and System Sciences, Vol. 6 No. 12, 2013, pp. 513-518. doi: 10.4236/ijcns.2013.612055.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	I. V. Semushin, “Adaptation in Stochastic Dynamic Systems—Survey and New Results I,” International Journal of Communications, Network and System Sciences, Vol. 4, No. 1, 2011, pp. 17-23. http://dx.doi.org/10.4236/ijcns.2011.41002
[2]	I. V. Semushin, “Adaptation in Stochastic Dynamic Systems—Survey and New Results II,” International Journal of Communications, Network and System Sciences, Vol. 4, No. 4, 2011, pp. 266-285. http://dx.doi.org/10.4236/ijcns.2011.44032
[3]	P. E. Caines, “Linear Stochastic Systems,” John Wiley and Sons, Inc., New York, 1988.
[4]	L. Ljung, “Convergence Analysis of Parametric Identification Methods,” IEEE Transactions on Automatic Control, Vol. 23, No. 5, 1978, pp. 770-783. http://dx.doi.org/10.1109/TAC.1978.1101840
[5]	E. Mosca, “Optimal, Predictive, and Adaptive Control,” Prentice Hall, Inc., Englewood Cliffs, 1995.
[6]	I. V. Semushin, J. V. Tsyganova and A. G. Skovikov, “Identification of a Simple Homeostasis Stochastic Model Based on Active Principle of Adaptation,” Book of Abstracts Applied Stochastic Models and Data Analysis ASMDA 2013 & Demographics, Barcelona, 25-28 June 2013, p. 191.