Using singular value decomposition for generalized linear autoregression of signals
Autoregressive models (AR) are fundamental for analysis, representation, and prediction of signals. AR modelling uses the premise that past signal values influence current ones. This influence is causal and is modelled as a linear superposition, because a weighted addition of past values is used. Th...
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| Format: | Article |
| Language: | English |
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De Gruyter
2018-09-01
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| Series: | Current Directions in Biomedical Engineering |
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| Online Access: | https://doi.org/10.1515/cdbme-2018-0090 |