Approximate error conjugation gradient minimization methods
Abstract
In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.
- Inventors:
- Issue Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1083968
- Patent Number(s):
- 8447565
- Application Number:
- 12/795,560
- Assignee:
- Lawrence Livermore National Security, LLC (Livermore, CA)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- DOE Contract Number:
- AC52-07NA27344
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Kallman, Jeffrey S. Approximate error conjugation gradient minimization methods. United States: N. p., 2013.
Web.
Kallman, Jeffrey S. Approximate error conjugation gradient minimization methods. United States.
Kallman, Jeffrey S. Tue .
"Approximate error conjugation gradient minimization methods". United States. https://www.osti.gov/servlets/purl/1083968.
@article{osti_1083968,
title = {Approximate error conjugation gradient minimization methods},
author = {Kallman, Jeffrey S},
abstractNote = {In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue May 21 00:00:00 EDT 2013},
month = {Tue May 21 00:00:00 EDT 2013}
}
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