A non-extensive maximum entropy based regularization method for bad conditioned inverse problems

Laura Rebollo - Neira; A. Plastino; J. Fernandez-Rubio

doi:10.1016/S0378-4371(98)00400-2

A non-extensive maximum entropy based regularization method for bad conditioned inverse problems

Laura Rebollo - Neira, A. Plastino, J. Fernandez-Rubio

Research output: Contribution to journal › Article › peer-review

Abstract

A regularization method based on the non-extensive maximum entropy principle is devised. Special emphasis is given to the q=1/2 case. We show that, when the residual principle is considered as constraint, the q=1/2 generalized distribution of Tsallis yields a regularized solution for bad-conditioned problems. The so devised regularized distribution is endowed with a component which corresponds to the well known regularized solution of Tikhonov.

Original language	English
Pages (from-to)	555-568
Number of pages	14
Journal	Physica A
Volume	261
Issue number	3-4
DOIs	https://doi.org/10.1016/S0378-4371(98)00400-2
Publication status	Published - 15 Dec 1998

Bibliographical note

Keywords

regularization method
non-extensive maximum entropy principle
Tikhonov

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10.1016/S0378-4371(98)00400-2

A non-extensive maximum entropy based regularization method
Copyright © 1998 Published by Elsevier Science B.V. All rights reserved.
Accepted author manuscript, 227 KB

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AB - A regularization method based on the non-extensive maximum entropy principle is devised. Special emphasis is given to the q=1/2 case. We show that, when the residual principle is considered as constraint, the q=1/2 generalized distribution of Tsallis yields a regularized solution for bad-conditioned problems. The so devised regularized distribution is endowed with a component which corresponds to the well known regularized solution of Tikhonov.

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A non-extensive maximum entropy based regularization method for bad conditioned inverse problems

Abstract

Bibliographical note

Keywords

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