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RLS Wiener Smoother for Colored Observation Noise with Relation to Innovation Theory in Linear Discrete-Time Stochastic Systems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Nakamori, Seiichi |
| Copyright Year | 2013 |
| Abstract | Abstract— Almost estimators are designed for the white observation noise. In the estimation problems, rather than the white observation noise, there might be actual cases where the observation noise is colored. This paper, from the viewpoint of the innovation theory, based on the recursive least-squares (RLS) Wiener fixed-point smoother and filter for the colored observation noise, newly proposes the RLS Wiener fixed-interval s moothing algorithm in linear d iscretetime wide-sense stationary stochastic systems. The observation ) (k y is given as the sum of the signal |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.mecs-press.org/ijitcs/ijitcs-v5-n3/IJITCS-V5-N3-1.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Fixed-Point Number Image noise Least-Squares Analysis Recursion Recursive least squares filter Restless Legs Syndrome Stationary process Stochastic process |
| Content Type | Text |
| Resource Type | Article |
