Cargando…
A Penalized Linear and Nonlinear Combined Conjugate Gradient Method for the Reconstruction of Fluorescence Molecular Tomography
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines...
Autores principales: | Shang, Shang, Bai, Jing, Song, Xiaolei, Wang, Hongkai, Lau, Jaclyn |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2007
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267888/ https://www.ncbi.nlm.nih.gov/pubmed/18354740 http://dx.doi.org/10.1155/2007/84724 |
Ejemplares similares
-
Nonlinear conjugate gradient methods for unconstrained optimization
por: Andrei, Neculai
Publicado: (2020) -
A Fast Reconstruction Algorithm for Fluorescence Optical
Diffusion Tomography Based on Preiteration
por: Song, Xiaolei, et al.
Publicado: (2007) -
Fitting linear models: an application of conjugate gradient algorithms
por: Mclntosh, Allen
Publicado: (1982) -
Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction
por: Fridovich-Keil, Sara, et al.
Publicado: (2023) -
A family of conjugate gradient methods for large-scale nonlinear equations
por: Feng, Dexiang, et al.
Publicado: (2017)