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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mao Lin Deng Zili |
| Copyright Year | 2007 |
| Description | Author affiliation: Harbin Eng. Univ., Harbin (Mao Lin) |
| Abstract | By the modern time series analysis methods, based on ARMA innovation model and augmented state space model, a multisensor optimal information fusion Wiener deconvolution predictor weighted by scalars is proposed. The formulas of computing the local predictor error variances and cross-covariances are given, which are applied to compute optimal weighting coefficients. Compared to the single sensor case, the accuracy of the fused predictor is improved. A simulation example shows its effectiveness. |
| Starting Page | 120 |
| Ending Page | 123 |
| File Size | 438972 |
| Page Count | 4 |
| File Format | |
| ISBN | 9787811240559 |
| DOI | 10.1109/CHICC.2006.4346816 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-07-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Deconvolution Multisensor Information Fusion Wiener Deconvolusion Predictor Optimal Fusion Rule Weighted by Scalars |
| Content Type | Text |
| Resource Type | Article |
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