| Автор | JIANG, J. |
| Автор | DORAISWAMI, R. |
| Дата выпуска | 1988 |
| dc.description | It is demonstrated that when the system to be identified is blockwise decomposable, additional advantages can be obtained by blockwise identification with recursive least-squares (RLS) identification algorithms. The following aspects are considered: (a) reduced computational burden; (b) lessened memory storage; (c) relaxed severity of the richness requirement on the exogenous input signals. The price paid for all these is the additional number of sensors used to tap the intermediate system states. |
| Формат | application.pdf |
| Издатель | Taylor & Francis Group |
| Копирайт | Copyright Taylor and Francis Group, LLC |
| Название | Direct and blockwise identification of decomposable systems using recursive least-squares algorithm |
| Тип | research-article |
| DOI | 10.1080/00207728808547124 |
| Electronic ISSN | 1464-5319 |
| Print ISSN | 0020-7721 |
| Журнал | International Journal of Systems Science |
| Том | 19 |
| Первая страница | 2441 |
| Последняя страница | 2447 |
| Выпуск | 12 |
| Библиографическая ссылка | GOODWIN, G. C. and PAYNE, R. L. 1977. Dynamic System Identification: Experiment Design and Data Analysis, New York: Academic Press. |
| Библиографическая ссылка | GOODWIN, G. C. and SIN, K. S. 1984. Adaptive Filtering Prediction and Control, Englewood Cliffs, NJ: Prentice Hall. |
