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

Rebollo - Neira, Laura, Plastino, A. and Fernandez-Rubio, J. (1998). A non-extensive maximum entropy based regularization method for bad conditioned inverse problems. Physica A, 261 (3-4), pp. 555-568.

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.

Publication DOI: https://doi.org/10.1016/S0378-4371(98)00400-2
Divisions: Engineering & Applied Sciences > Mathematics
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Additional Information: Copyright © 1998 Published by Elsevier Science B.V. All rights reserved.
Uncontrolled Keywords: regularization method,non-extensive maximum entropy principle,Tikhonov
Full Text Link:
Related URLs: http://www.else ... ion#description (Publisher URL)
Published Date: 1998-12-15
Authors: Rebollo - Neira, Laura ( 0000-0002-7420-8977)
Plastino, A.
Fernandez-Rubio, J.

Download

[img]

Version: Accepted Version

| Preview

Export / Share Citation


Statistics

Additional statistics for this record