Neural algorithm for solving differential equations

Finite difference equations are considered to solve differential equations numerically by utilizing minimization algorithms. Neural minimization algorithms for solving the finite difference equations are presented. Results of numerical simulation are described to demonstrate the method. Methods of i...

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Bibliographic Details
Published inJournal of computational physics Vol. 91; no. 1; pp. 110 - 131
Main Authors Lee, Hyuk, Kang, In Seok
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier Inc 01.11.1990
Elsevier
Subjects
Exact sciences and technology
Mathematical methods in physics
Numerical approximation and analysis
Physics
Finite difference equation
Differential equation
Numerical solution
Neural network
Algorithm
Implementation
Hopfield model
Convergence
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ISSN0021-9991
1090-2716
1090-2716
DOI10.1016/0021-9991(90)90007-N

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Summary:Finite difference equations are considered to solve differential equations numerically by utilizing minimization algorithms. Neural minimization algorithms for solving the finite difference equations are presented. Results of numerical simulation are described to demonstrate the method. Methods of implementing the algorithms are discussed. General features of the neural algorithms are discussed.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0021-9991
1090-2716
1090-2716
DOI:10.1016/0021-9991(90)90007-N