Elsevier

Information Sciences

Volume 17, Issue 3, April 1979, Pages 177-193
Information Sciences

Partitioning filters

https://doi.org/10.1016/0020-0255(79)90016-1Get rights and content

Abstract

In this paper a fundamentally new and computationally attractive class of linear filters—the partitioned filters—are presented and their important properties are briefly discussed. Specifically, it is shown that the partitioned filters constitute a powerful and unifying framework for linear estimation, posses a naturally parallel-processing structure, and yield numerically effective, robust, and fast estimation algorithms. As such, the partitioned filters constitute attractive alternatives to previous estimation algorithms such as the Kalman filter.

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