Applications of the periodogram method for perturbed block toeplitz satrices in statistical signal processing
In this paper, we combine the periodogram method for perturbed block Toeplitz matrices with the Cholesky decomposition to give a parameter estimation method for any perturbed vector autoregressive (VAR) or vector moving average (VMA) process, when we only know a perturbed version of the sequence of...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universidad de Navarra |
| Repositorio: | Dadun. Depósito Académico Digital de la Universidad de Navarra |
| Idioma: | inglés |
| OAI Identifier: | oai:dadun.unav.edu:10171/65220 |
| Acceso en línea: | https://hdl.handle.net/10171/65220 |
| Access Level: | acceso abierto |
| Palabra clave: | Parameter estimation Periodogram method for perturbed block Toeplitz matrices The Cholesky decomposition Vector autoregressive (VAR) processes Vector moving average (VMA) processes |
| Sumario: | In this paper, we combine the periodogram method for perturbed block Toeplitz matrices with the Cholesky decomposition to give a parameter estimation method for any perturbed vector autoregressive (VAR) or vector moving average (VMA) process, when we only know a perturbed version of the sequence of correlation matrices of the process. In order to combine the periodogram method for perturbed block Toeplitz matrices with the Cholesky decomposition, we first need to generalize a known result on the Cholesky decomposition of Toeplitz matrices to perturbed block Toeplitz matrices. |
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