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Showing papers by "Enrique Alba published in 1995"


01 Jan 1995
TL;DR: In this paper, the authors present the KF in an attractive way to economists by using information theory and Bayesian inference, and show that most of its important results have been published in engineering journals with language, notation and style proper of engineers.
Abstract: Almost since its appearance, the Kalman Filter (KF) has been successfully used in control engineering. Unfor­ tunately, most of its important results have been publish­ ed in engineering journals with language, notation and style proper of engineers. In this paper, we want to present the KF in an attractive way to economists by using information theory and Bayesian inference.

20 citations


Posted Content
TL;DR: In this paper, the authors present the Kalman Filter in an attractive way to economists by using information theory and Bayesian inference, and present the KF in an approach similar to ours.
Abstract: Almost since its appearance, the Kalman Filter (KF) has been successfully used in control engineering Unfor­ tunately, most of its important results have been publish­ ed in engineering journals with language, notation and style proper of engineers In this paper, we want to present the KF in an attractive way to economists by using information theory and Bayesian inference

14 citations


Book ChapterDOI
01 Jan 1995
TL;DR: This work has tackled the problem of assigning the processes to processors in a multiprocessors system by using a GA that works on a specific fitness function that allows to meet these goals.
Abstract: Datalog is a query language for deductive databases. This language allows to evaluate a query incrementally on a network of processes. The tuples flow among them in parallel in order to compute the solution to the query. A major issue in this evaluation is the problem of assigning the processes to processors in a multiprocessors system. Not only load balancing is wanted but lowering the communication costs among the processors is crucial. We have tackled this problem by using a GA that works on a specific fitness function that allows to meet these goals. The techniques and results are presented here.

2 citations