Optimal Adaptive Estimation: Structure and Parameter Adaptation

IEEE Transactions on Automatic Control

Volumn 16, Issue 2, 1971, Pages 160-170

  Lainiotis, Demetrios G ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC CONTROL; IETAA; KALMAN FILTERS; OPTIMIZATION; PARAMETER ESTIMATION; STATE ESTIMATION; SYSTEMS IDENTIFICATION;

EID: 0015039116     PISSN: 00189286     EISSN: 15582523     Source Type: Journal    
DOI: 10.1109/TAC.1971.1099684     Document Type: Note

References (7)

1. D. T. Magill, “Optimal adaptive estimation of sampled stochastic processes,” IEEE Trans. Automat. Contr., vol. AC-10, Oct. 1965, pp. 434–439.
2. D. G. Lainiotis and C. G. Hilborn, “Learning systems for minimum risk adaptive pattern classfication and optimal adaptive estimation,” Communication Systems Research Group, Dep. Elec. Eng., Univ, of Texas, Austin, Tech. Rep. 67–9, DDC Document AD-663702, Nov. 1967.
3. C. G. Hilborn and D. G. Lainiotis, “Optimal estimation in the presence of unknown parameters,” IEEE Trans. Syst. Sci. Cybern., vol. SSC-5, Jan. 1969, pp. 38–43.
4. D. G. Lainiotis, “On Kalman filter design,” Southwestern IEEE Conf. Rec. (Abstract), Houston, Tex., Apr. 1968.
5. R. S. Bucy and P. D. Joseph, Filtering for Stochastic Processes with Application to Guidance. New York: wiley, 1968.
6. T. Kailath, “A general likelihood-ratio formula for random signals in Gaussian noise,” IEEE Trans. Inform. Theory, vol. IT-15, May 1969, pp. 350–361.
7. R. L. Sengbush and D. G. Lainiotis, “Simplified parameter quantization procedure,” IEEE Trans. Automat Contr. (Corresp.) Aug. AC-14 1969 pp. 424-425.