Matrix Theory and Algorithms

Matrix Theory and Algorithms is a research topic within Computational Theory and Mathematics. Science Explorer counts 50k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on matrix algorithms, iterative methods, and numerical techniques for solving eigenvalue problems, preconditioning sparse linear systems, and addressing saddle point problems. It covers topics such as Krylov subspace methods, structured preconditioners, parallel computing, and numerical linear algebra.

• Matrix Computations
• Numerical Linear Algebra
• Preconditioning Techniques
• Iterative Methods
• Eigenvalue Problems
• Sparse Linear Systems
• Krylov Subspace Methods
• Saddle Point Problems
• Structured Preconditioners
• Parallel Computing