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CRLB under K-distributed observation with parameterized mean

Abstract : A semi closed-form expression of the Fisher information matrix in the context of K-distributed observations with parameterized mean is given and related to the classical, i.e. Gaussian case. This connection is done via a simple multiplicative factor, which only depends on the intrinsic parameters of the texture and the size of the observation vector. Finally, numerical simulation is provided to corroborate the theoretical analysis
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Contributor : Alexandre Renaux <>
Submitted on : Monday, May 19, 2014 - 3:04:56 PM
Last modification on : Tuesday, April 20, 2021 - 4:54:04 PM
Long-term archiving on: : Monday, April 10, 2017 - 11:46:36 PM


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  • HAL Id : hal-00993010, version 1


Mohammed Nabil El Korso, Alexandre Renaux, Philippe Forster. CRLB under K-distributed observation with parameterized mean. IEEE Sensor Array Multichannel Workshop, Jun 2014, A Coruña, Spain. ⟨hal-00993010⟩



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