Research output: Contribution to conference › Paper › peer-review
The work is devoted to the mathematical theory of the 'Caterpillar' method which has proved to be a very powerful tool of analysis of time series. This method is based on the use of the principal component analysis technique applied to a multivariate sample which is obtained from the initial sample by the method of delays. A natural language used to analyse the method is the Hilbert-Schmidt operator theory. We give conditions when two deterministic functions are completely separated from each other for a finite period of observations. We also show that under mild conditions any deterministic function can be asymptotically separated from any ergodic random noise.
Original language | English |
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Pages | 395-397 |
Number of pages | 3 |
State | Published - 1996 |
Event | Proceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96 - Corfu, Greece Duration: 24 Jun 1996 → 26 Jun 1996 |
Conference | Proceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96 |
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City | Corfu, Greece |
Period | 24/06/96 → 26/06/96 |
ID: 76337470