An ML/MMSE estimation approach to blind equalization

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 4, Issue , 1994, Pages IV569-IV572

  Shao, Min ^a   Nikias, Chrysoatomos L ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRICAL ENGINEERING; SIGNAL PROCESSING;

CHANNEL COEFFICIENT; DATA SEQUENCES; EM ALGORITHMS; ESTIMATION APPROACHES; ML ESTIMATE; MMSE ESTIMATION; RANDOM DATA SEQUENCE;

BLIND EQUALIZATION;

EID: 0345527667     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.1994.389753     Document Type: Conference Paper

References (7)

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2. M. Ghosh, An Optimal Approach to Blind Equalization. PhD thesis, Univ. of Southern California, Los Angeles, CA, 1991.
3. M. Feder and J. A. Catipovic, "Algorithms for joint channel estimating and data recovery - application to equalization in underwater communications,'' IEEE J. Oceanic Eng., vol. 16, pp. 42-55, Jan. 1991.
4. K. Giridhar, J. J. Shynk, and R. A. litis, "Bayesian/decision-feedback algorithm for blind deconvolution," Opt. Eng., vol. 31, pp. 1211-1223, June 1992.
5. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Roy. Statist. Soc. Ser. B, vol. 39, pp. 1-39, 1977.
6. C. F. Wu, "On the convergence properties of the EM algorithms," Ann. Statist., vol. 11, pp. 95-103, 1983.
7. J. M. Mendel, Lessons in Digital Estimation Theory. Englewood Cliffs, NJ: Prentice-Hall, 1987.