Blind Minimax Estimation

Improving MSE over Least Squares

References

[1] Z. Ben-Haim and Y. C. Eldar, “Blind minimax estimation,” IEEE Trans. Information
Theory, vol. 53, no. 9, pp. 3145-3157, Sep. 2007.

[2] Y. C. Eldar, A. Ben-Tal, and A. Nemirovski, “Robust mean-squared error estimation in the presence of model uncertainties,” IEEE Trans. Signal Process., vol. 53, no. 1, pp.
168-181, Jan. 2005.

[3] A. Elron, G. Leibovitz, Z. Ben-Haim, and Y. C. Eldar, "Recursive Blind Minimax Estimation: Improving MSE over Recursive Least Squares," to appear in 25th IEEE
Convention of Electrical and Electronics Engineers in Israel (IEEEI'08), December
2008.

[4] J.H. Manton, V. Krishnamurty and H.V. Poor, “James-Stein state filtering algorithms,”
IEEE Trans. Signal Process., vol. 46, no. 9, pp. 2431-2447, Sep. 1998.

[5] C. Stein, “Inadmissibility of the usual estimator for the mean of a multivariate distribution,” Proc. 3rd Berkeley Symp. Mathematical Statistics and Probability,
Berkeley, CA, 1956, vol. 1, pp. 197-206.

[6] M. E. Bock, “Minimax estimators of the mean of a multivariate normal distribution,"
             Ann. Statist., vol. 3, no. 1, pp. 209–218, Jan. 1975.

Links

Zvika Ben-Haim

Prof. Yonina Eldar

Signal and Image Processing Lab

Project supervisor

Academic supervisor

Downloads

Matlab package

Implementation of the different versions of the blind minimax estimator. This package can be used to reproduce all the examples in this website, along with additional means of comparison between methods.