Optimal filtering in singular spectrum analysis
Singular spectrum analysis (SSA) provides a robust method of separating an arbitrary signal from "white" (independent, identically distributed) noise. In the presence of "coloured" noise, or any autocorrelated process, high-variance components of the noise can confuse the singula...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
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1997
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| _version_ | 1797085327823732736 |
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| author | Allen, M Smith, L |
| author_facet | Allen, M Smith, L |
| author_sort | Allen, M |
| collection | OXFORD |
| description | Singular spectrum analysis (SSA) provides a robust method of separating an arbitrary signal from "white" (independent, identically distributed) noise. In the presence of "coloured" noise, or any autocorrelated process, high-variance components of the noise can confuse the singular value decomposition, thereby obscuring genuine signals which are, in principle, detectable. A generalization of SSA is presented which yields both an optimal filter to discriminate against an arbitrary coloured noise and an objective method of quantifying uncertainty in signal reconstruction. The algorithm is applied to a simple synthetic signal-separation problem and used to resolve a degeneracy in the SSA of interannual and interdecadal variability of the Earth's global mean temperature. © 1997 Elsevier Science B.V. |
| first_indexed | 2024-03-07T02:07:23Z |
| format | Journal article |
| id | oxford-uuid:9f71c9ee-359f-4460-9229-6260ddc63b56 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:07:23Z |
| publishDate | 1997 |
| record_format | dspace |
| spelling | oxford-uuid:9f71c9ee-359f-4460-9229-6260ddc63b562022-03-27T00:57:51ZOptimal filtering in singular spectrum analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9f71c9ee-359f-4460-9229-6260ddc63b56EnglishSymplectic Elements at Oxford1997Allen, MSmith, LSingular spectrum analysis (SSA) provides a robust method of separating an arbitrary signal from "white" (independent, identically distributed) noise. In the presence of "coloured" noise, or any autocorrelated process, high-variance components of the noise can confuse the singular value decomposition, thereby obscuring genuine signals which are, in principle, detectable. A generalization of SSA is presented which yields both an optimal filter to discriminate against an arbitrary coloured noise and an objective method of quantifying uncertainty in signal reconstruction. The algorithm is applied to a simple synthetic signal-separation problem and used to resolve a degeneracy in the SSA of interannual and interdecadal variability of the Earth's global mean temperature. © 1997 Elsevier Science B.V. |
| spellingShingle | Allen, M Smith, L Optimal filtering in singular spectrum analysis |
| title | Optimal filtering in singular spectrum analysis |
| title_full | Optimal filtering in singular spectrum analysis |
| title_fullStr | Optimal filtering in singular spectrum analysis |
| title_full_unstemmed | Optimal filtering in singular spectrum analysis |
| title_short | Optimal filtering in singular spectrum analysis |
| title_sort | optimal filtering in singular spectrum analysis |
| work_keys_str_mv | AT allenm optimalfilteringinsingularspectrumanalysis AT smithl optimalfilteringinsingularspectrumanalysis |