## Abstract

The problem of mixed H_{2}/H_{∞} robust deconvolution of linear discrete-time stationary processes is considered where the parameters of the process are partially known. Using the state space model of the system, the state space matrices are assumed to reside in a given polytope. A stationary deconvolver is obtained which achieves a preassigned input estimation level for all the matrices in the uncertainty polytope. The suggested synthesis technique for the deconvolution filters applies a recent parameter dependent Lyapunov approach to compute the H_{2} and H _{∞} norms of the transfer function matrix which relates the driving process and noise signals to the dynamically weighted error signal and a multi-objective evolutionary algorithm to find an estimate of the Pareto front which describes the trade-off between these two norms.

Original language | English |
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Pages | 56-59 |

Number of pages | 4 |

State | Published - 2004 |

Event | 2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings - Tel-Aviv, Israel Duration: 6 Sep 2004 → 7 Sep 2004 |

### Conference

Conference | 2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings |
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Country/Territory | Israel |

City | Tel-Aviv |

Period | 6/09/04 → 7/09/04 |

## Keywords

- Evolutionary algorithms
- Genetic algorithms
- H deconvolution
- Mixed H /H deconvolution
- Multi-objective
- Polytopic uncertainty

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