### Abstract

In this paper, multiscale representation of data is utilized to reduce the collinearity problem often encountered in Finite Impulse Response (FIR) modeling. The idea is to decompose the input-output data at multiple scales, use the scaled signal approximations of the data to construct a FIR model at each scale, and then select among all scales the optimum estimated FIR model. The rationale behind this approach is that the number of significant cross correlation function (CCF) coefficients estimated using the scaled signal approximations of the input-output data decreases at coarser scales. This means that more parsimonious FIR models, with less collinearity and improved estimation accuracy, can be constructed at coarser scales. Of course, the estimation accuracy will deteriorate at very coarse scales. Therefore, it is very important to select the most appropriate scale for modeling purposes, which can be done by selecting the scale which results in the maximum prediction signal to noise ratio. The developed multiscale FIR modeling approach is shown to outperform existing methods, such as ordinary least squares (OLS) regression and ridge regression (RR).

Original language | English |
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Title of host publication | Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 |

Pages | 8162-8167 |

Number of pages | 6 |

DOIs | |

Publication status | Published - 1 Dec 2005 |

Event | 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 - Seville, Spain Duration: 12 Dec 2005 → 15 Dec 2005 |

### Publication series

Name | Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 |
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Volume | 2005 |

### Other

Other | 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 |
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Country | Spain |

City | Seville |

Period | 12/12/05 → 15/12/05 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05*(pp. 8162-8167). [1583483] (Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05; Vol. 2005). https://doi.org/10.1109/CDC.2005.1583483