This paper sketches the main research developments in the area of computational meth ods for eigenvalue problems during the 20th century. The earliest of such methods dates back to work of Jacobi in the middle of the nineteenth century. Since computing eigenvalues and vectors is essentially more complicated than solving linear systems, it is not surprising that highly significant developments in this area started with the introduction of electronic computers around 1950. In the early decades of this century, however, important theoretical developments had been made from which computational techniques could grow. Research in this area of numerical linear algebra is very active, since there is a heavy demand for solving compl...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
Matrix algorithms are at the core of scientific computing and are indispensable tools in most applic...
This chapter is about eigenvalues and singular values of matrices. Computational algorithms and sens...
This paper sketches the main research developments in the area of computational meth ods for eige...
AbstractThis paper sketches the main research developments in the area of computational methods for ...
This paper sketches the main research developments in the area of computational meth-ods for eigenva...
Linear eigenproblems continue to be an important and highly relevant area of research in numerical l...
Abstract. We briefly survey some of the classical methods for the numerical so-lution of eigenvalue ...
Many fields make use of the concepts about eigenvalues in their studies. In engineering, physics, st...
AbstractThis paper sketches the main research developments in the area of iterative methods for solv...
This paper sketches the main research developments in the area of iterative methods for solving li...
AbstractNumerical methods for the solution of initial value problems in ordinary differential equati...
This thesis treats a number of aspects of subspace methods for various eigenvalue problems. Vibrat...
We give an elementary exposition of the Lanczos technique to solve the matrix eigenvalue problem. Th...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68981/2/10.1177_003754976400300310.pd
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
Matrix algorithms are at the core of scientific computing and are indispensable tools in most applic...
This chapter is about eigenvalues and singular values of matrices. Computational algorithms and sens...
This paper sketches the main research developments in the area of computational meth ods for eige...
AbstractThis paper sketches the main research developments in the area of computational methods for ...
This paper sketches the main research developments in the area of computational meth-ods for eigenva...
Linear eigenproblems continue to be an important and highly relevant area of research in numerical l...
Abstract. We briefly survey some of the classical methods for the numerical so-lution of eigenvalue ...
Many fields make use of the concepts about eigenvalues in their studies. In engineering, physics, st...
AbstractThis paper sketches the main research developments in the area of iterative methods for solv...
This paper sketches the main research developments in the area of iterative methods for solving li...
AbstractNumerical methods for the solution of initial value problems in ordinary differential equati...
This thesis treats a number of aspects of subspace methods for various eigenvalue problems. Vibrat...
We give an elementary exposition of the Lanczos technique to solve the matrix eigenvalue problem. Th...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68981/2/10.1177_003754976400300310.pd
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
Matrix algorithms are at the core of scientific computing and are indispensable tools in most applic...
This chapter is about eigenvalues and singular values of matrices. Computational algorithms and sens...