Near-ideal causal smoothing filters for the real sequences
The paper considers causal smoothing of the real sequences, i.e., discrete time processes in a deterministic setting. A family of causal linear time-invariant filters is suggested. These filters approximate the gain decay for some non-causal ideal smoothing filters with transfer functions vanishing...
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| Format: | Journal Article |
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Elsevier BV
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/46183 |
| _version_ | 1848757488080388096 |
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| author | Dokuchaev, Nikolai |
| author_facet | Dokuchaev, Nikolai |
| author_sort | Dokuchaev, Nikolai |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The paper considers causal smoothing of the real sequences, i.e., discrete time processes in a deterministic setting. A family of causal linear time-invariant filters is suggested. These filters approximate the gain decay for some non-causal ideal smoothing filters with transfer functions vanishing at a point of the unit circle and such that they transfer processes into predictable ones. In this sense, the suggested filters are near-ideal; a faster gain decay would lead to the loss of causality. Applications to predicting algorithms are discussed and illustrated by experiments with forecasting of autoregressions with the coefficients that are deemed to be untraceable. |
| first_indexed | 2025-11-14T09:28:53Z |
| format | Journal Article |
| id | curtin-20.500.11937-46183 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:28:53Z |
| publishDate | 2015 |
| publisher | Elsevier BV |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-461832017-09-13T16:00:28Z Near-ideal causal smoothing filters for the real sequences Dokuchaev, Nikolai predicting near-ideal filters casual filters LTI filters smoothing filters The paper considers causal smoothing of the real sequences, i.e., discrete time processes in a deterministic setting. A family of causal linear time-invariant filters is suggested. These filters approximate the gain decay for some non-causal ideal smoothing filters with transfer functions vanishing at a point of the unit circle and such that they transfer processes into predictable ones. In this sense, the suggested filters are near-ideal; a faster gain decay would lead to the loss of causality. Applications to predicting algorithms are discussed and illustrated by experiments with forecasting of autoregressions with the coefficients that are deemed to be untraceable. 2015 Journal Article http://hdl.handle.net/20.500.11937/46183 10.1016/j.sigpro.2015.07.002 Elsevier BV fulltext |
| spellingShingle | predicting near-ideal filters casual filters LTI filters smoothing filters Dokuchaev, Nikolai Near-ideal causal smoothing filters for the real sequences |
| title | Near-ideal causal smoothing filters for the real sequences |
| title_full | Near-ideal causal smoothing filters for the real sequences |
| title_fullStr | Near-ideal causal smoothing filters for the real sequences |
| title_full_unstemmed | Near-ideal causal smoothing filters for the real sequences |
| title_short | Near-ideal causal smoothing filters for the real sequences |
| title_sort | near-ideal causal smoothing filters for the real sequences |
| topic | predicting near-ideal filters casual filters LTI filters smoothing filters |
| url | http://hdl.handle.net/20.500.11937/46183 |