Published July 1994
| Version v1
Journal article
Bayesian probability theory and inverse problems
Description
Bayesian probability theory is applied to approximate solving of the inverse problems. In order to solve the moment problem with the noisy data, the entropic prior is used. The expressions for the solution and its error bounds are presented. When the noise level tends to zero, the Bayesian solution tends to the classic maximum entropy solution in the L2 norm. The way of using spline prior is also shown. (author)
Additional details
Publishing Information
- Journal Title
- Acta Physica Polonica. Series B
- Journal Volume
- B25
- Journal Issue
- 7
- Journal Page Range
- p. 1099-1108.
- ISSN
- 0587-4254
- CODEN
- APOBBB
INIS
- Country of Publication
- Poland
- Country of Input or Organization
- Poland
- INIS RN
- 29002595
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- CALCULATION METHODS; DIFFERENTIAL EQUATIONS; ENTROPY; INTEGRAL EQUATIONS; MOMENTS METHOD
- Descriptors DEC
- EQUATIONS; PHYSICAL PROPERTIES; THERMODYNAMIC PROPERTIES
Optional Information
- Contract/Grant/Project number
- KBN Grant No 2P30207904
- Notes
- 11 refs.
- Funding organization
- Polish Committee for Scientific Research, Warsaw (Poland).