Geophysical measurements can often be described in terms of multichannel, autoregressive data models from which one can directly derive measures of the harmonic composition of the underlying geophysical process and its inherent self-predictability. / We explore methods for and uses of multichannel autoregressive data modelling in a geophysical context. / Autoregressive data modelling using the least-squares linear prediction method is generalized to multichannel time series. A recursive algorithm is obtained for the formation of the system of multichannel normal equations which determine the least-squares solution of the multichannel linear prediction problem. Solution of these multichannel normal equations is accomplished by the Cholesky factorization method. / The corresponding multichannel Maximum Entropy spectra derived from these least-squares estimates of the autoregressive model parameters are compared to that obtained using those parameters estimated by a multichannel generalization of Burg's algorithm. Numerical experiments have shown that the multichannel spectra obtained using the least-squares method provides for more accurate frequency determination for truncated sinusoids in the presence of additive white noise.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.71838 |
| Date | January 1983 |
| Creators | Tyraskis, Panagiotis A. |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (Department of Mining and Metallurgical Engineering.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 000166996, proquestno: AAINK64554, Theses scanned by UMI/ProQuest. |
Page generated in 0.0019 seconds