article · Proceedings of the IEEE · 1988
The cascade EM algorithm
Cited by 15Abstract and details only
Abstract
The estimate-maximize (EM) algorithm is an iterative method for finding maximum-likelihood parameter estimates from incomplete data. The authors develop an extension of the EM algorithm that may be useful in accelerating the algorithm and in simplifying the computations involved. The extension works with an intermediate complete data specification, and performs intermediate steps at some iterations. The authors consider the problem of parameter identification of a continuous-time linear dynamic system given discrete-time observations, and show that the proposed algorithm accelerates the convergence of the EM algorithm and simplifies the computations involved.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite this paper
Segal, M., & Weinstein, E. (1988). The cascade EM algorithm. Proceedings of the IEEE, 76(10), 1388–1390. https://doi.org/10.1109/5.16341
Segal, M., and E. Weinstein. “The cascade EM algorithm.” Proceedings of the IEEE, vol. 76, no. 10, 1988, pp. 1388–90, https://doi.org/10.1109/5.16341.
Segal, M., and E. Weinstein. 1988. “The cascade EM algorithm.” Proceedings of the IEEE 76 (10): 1388–90. https://doi.org/10.1109/5.16341.
Segal, M. and Weinstein, E. (1988) ‘The cascade EM algorithm’, Proceedings of the IEEE, 76(10), pp. 1388–1390. Available at: https://doi.org/10.1109/5.16341.
@article{segal1988cascade,
title = {{The cascade EM algorithm}},
author = {Segal, M. and Weinstein, E.},
journal = {Proceedings of the IEEE},
volume = {76},
number = {10},
pages = {1388--1390},
year = {1988},
doi = {10.1109/5.16341}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.