| 書目名稱 | Lectures on Discrete Time Filtering |
| 編輯 | R. S. Bucy |
| 視頻video | http://file.papertrans.cn/584/583499/583499.mp4 |
| 叢書名稱 | Signal Processing and Digital Filtering |
| 圖書封面 |  |
| 描述 | The theory of linear discrete time filtering started with a paper by Kol- mogorov in 1941. He addressed the problem for stationary random se- quences and introduced the idea of the innovations process, which is a useful tool for the more general problems considered here. The reader may object and note that Gauss discovered least squares much earlier; however, I want to distinguish between the problem of parameter estimation, the Gauss problem, and that of Kolmogorov estimation of a process. This sep- aration is of more than academic interest as the least squares problem leads to the normal equations, which are numerically ill conditioned, while the process estimation problem in the linear case with appropriate assumptions leads to uniformly asymptotically stable equations for the estimator and the gain. The conditions relate to controlability and observability and will be detailed in this volume. In the present volume, we present a series of lectures on linear and nonlinear sequential filtering theory. The theory is due to Kalman for the linear colored observation noise problem; in the case of white observation noise it is the analog of the continuous-time Kalman-Bucy theory. The d |
| 出版日期 | Textbook 1994 |
| 關鍵詞 | Signal; electrical engineering; geophysics; numerical analysis; physics |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4613-8392-5 |
| isbn_softcover | 978-1-4613-8394-9 |
| isbn_ebook | 978-1-4613-8392-5Series ISSN 1431-7893 |
| issn_series | 1431-7893 |
| copyright | Springer-Verlag New York, Inc. 1994 |
|Archiver|手機版|小黑屋|
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