A General Approach to Linear Mean-Square Estimation Problems

IEEE Transactions on Information Theory

Volumn 19, Issue 1, 1973, Pages 110-114

  Cambanis, Stamatis ^a  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROBABILITY - RANDOM PROCESSES;

MEAN-SQUARE ESTIMATION;

INFORMATION THEORY;

METHODOLOGY; SIGNAL DETECTION; SIGNAL NOISE RATIO; STATISTICS; THEORETICAL STUDY;

EID: 0015534497     PISSN: 00189448     EISSN: 15579654     Source Type: Journal    
DOI: 10.1109/TIT.1973.1054943     Document Type: Article

References (12)

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2. S. Cambanis and E. Masry, “On the representation of weakly continuous processes,” Inform. Sci., vol. 3, pp. 277-290, 1971.
3. S. Cambanis, “Bases in L 2 spaces with applications to stochastic processes with orthogonal increments,” Proc. Amer. Math. Soc., vol. 29, pp. 284–290, 1971.
4. V. S. Pugachev, Theory of Random Functions. Oxford, England: Pergamon, 1965.
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7. H. Dym and H. P. McKean, “Extrapolation and interpolation of stationary Gaussian processes,” Ann. Math. Stat., vol. 41, pp. 1817–1844, 1970.
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10. T. T. Kadota, “Optimum estimation of nonstationary Gaussian signals in noise,” IEEE Trans. Inform. Theory, vol. IT-15, pp. 253–257, Mar. 1969.
11. H. L. Van Trees, “Analog communication over randomly-time-varying channels,” IEEE Trans. Inform. Theory, vol. IT-12, pp. 51–63, Jan. 1966.
12. I. Bar-David, “Estimation of linear weighting functions in Gaussian noise,” IEEE Trans. Inform. Theory, vol. IT-14, pp. 395–407, May 1968.