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Dynamic estimation of a noise over estimation factor for Jacobian-based adaptation
Abstract : In this paper we propose an enhancement of the Jacobian adaptation by estimating automatically a noise over estimation factor which yields to a closer approximation of Parallel model combination (PMC) than the traditional Jacobian adaptation. Noise over estimation factors are estimated at run-time for a set of clustered Gaussians obtained on the training set. Experiments conducted on a French natural number database show that similar performance as PMC can be obtained at the expense of a slight increase in computational complexity as compared to Jacobian adaptation.
Cited literature [4 references]
https://hal.inria.fr/inria-00107578
Contributor : Publications Loria <>
Submitted on : Thursday, October 19, 2006 - 9:02:02 AM
Last modification on : Tuesday, September 24, 2019 - 4:00:13 PM
Document(s) archivé(s) le : Wednesday, March 29, 2017 - 1:01:21 PM
Contributor : Publications Loria <>
Submitted on : Thursday, October 19, 2006 - 9:02:02 AM
Last modification on : Tuesday, September 24, 2019 - 4:00:13 PM
Document(s) archivé(s) le : Wednesday, March 29, 2017 - 1:01:21 PM