Abstract | ||
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A procedure is given for optimizing the sequential estimation of a random variable in the mean-square sense, with the constraint that the data must be summarized by a finite-valued statistic. This finite-valued statistic can be considered to be the memory of the processor. The estimate is constrained to be a function of the contents of the memory and the time of the estimate. An example is given to illustrate the results. |
Year | DOI | Venue |
---|---|---|
1973 | 10.1109/TIT.1973.1055080 | Information Theory, IEEE Transactions |
Keywords | Field | DocType |
Finite-memory methods,Sequential estimation | Discrete mathematics,Random variable,Mathematical optimization,Statistic,Computer science,Algorithm,Sequential estimation | Journal |
Volume | Issue | ISSN |
19 | 5 | 0018-9448 |
Citations | PageRank | References |
5 | 1.10 | 3 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Koplowitz, Jack | 1 | 42 | 22.60 |
Roberts, R.A. | 2 | 5 | 1.10 |