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BARANKIN BOUND FOR MULTIPLE CHANGE-POINT ESTIMATION

Abstract : We derive the Barankin bound on the mean-squared error for multiple change-point estimation of an independent measurement sequence. We first derive a general form of this bound and give the structure of the so-called Barankin information matrix (BIM). We show that the BIMfor the change-point parameters has a tri-diagonal structure which means that one change-point estimation depends on its neighboring change points. Using this result, we propose a computationally efficient inversion algorithm of the BIM. As an illustration, we analyze the case of changes in the mean vector of a Gaussian distribution.
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https://hal.inria.fr/inria-00444824
Contributor : Alexandre Renaux <>
Submitted on : Thursday, January 7, 2010 - 12:35:05 PM
Last modification on : Thursday, June 17, 2021 - 3:49:21 AM
Long-term archiving on: : Friday, June 18, 2010 - 12:31:11 AM

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  • HAL Id : inria-00444824, version 1

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Patricio La Rosa, Alexandre Renaux, Arye Nehorai. BARANKIN BOUND FOR MULTIPLE CHANGE-POINT ESTIMATION. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP-2007, 2007, St. Thomas, US Virgin Island, United States. ⟨inria-00444824⟩

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