This book contains papers on sparse matrices and their appli cations which were presented at a Symposium held at the IBM Thomas J. Watson Research Center, Yorktown Heights, New York on September 9-10, 1971. This is a very active field of research since efficient techniques for handling sparse matrix calculations are an important aspect of problem solving. In large scale problems, the feasibility of the calculation depends critically on the efficiency of the underlying sparse matrix algorithms. An important feature of the conference and its proceedings is the cross-fertilization achieved among a broad spectrum of application areas, and among combinatorialists, numerical analysts, and computer scientists. The mathematical, programming, and data management features of these techniques provide a unifying theme which can benefit readers in many fields. The introduction summarizes the major ideas in each paper. These ideas are interspersed with a brief survey of sparse matrix technology. An extensive unified bibliography is provided for the reader interested in more systematic information. The editors wish to thank Robert K. Brayton for his many helpful suggestions as chairman of the organizing committee and Redmond O'Brien for his editorial and audio-visual assistance. We would also like to thank Mrs. Tiyo Asai and Mrs. Joyce Otis for their help during the conference and on the numerous typing jobs for the manuscript. A special thanks goes to William J. Turner for establishing the IBM Research Symposia Series with Plenum Press.

Klappentext

This book contains papers on sparse matrices and their appli­ cations which were presented at a Symposium held at the IBM Thomas J. Watson Research Center, Yorktown Heights, New York on September 9-10, 1971. This is a very active field of research since efficient techniques for handling sparse matrix calculations are an important aspect of problem solving. In large scale problems, the feasibility of the calculation depends critically on the efficiency of the underlying sparse matrix algorithms. An important feature of the conference and its proceedings is the cross-fertilization achieved among a broad spectrum of application areas, and among combinatorialists, numerical analysts, and computer scientists. The mathematical, programming, and data management features of these techniques provide a unifying theme which can benefit readers in many fields. The introduction summarizes the major ideas in each paper. These ideas are interspersed with a brief survey of sparse matrix technology. An extensive unified bibliography is provided for the reader interested in more systematic information. The editors wish to thank Robert K. Brayton for his many helpful suggestions as chairman of the organizing committee and Redmond O'Brien for his editorial and audio-visual assistance. We would also like to thank Mrs. Tiyo Asai and Mrs. Joyce Otis for their help during the conference and on the numerous typing jobs for the manuscript. A special thanks goes to William J. Turner for establishing the IBM Research Symposia Series with Plenum Press.

Inhalt
Symposium on Sparse Matrices and Their Applications.- Computational Circuit Design.- Eigenvalue Methods for Sparse Matrices.- Sparse Matrix Approach to the Frequency Domain Analysis of Linear Passive Electrical Networks.- Some Basic Technqiues for Solving Sparse Systems of Linear Equations.- Vector and Matrix Variability Type in Sparse Matrix Algorithms.- Linear Programming.- The Partitioned Preassigned Pivot Procedure (P4).- Modifying Triangular Factors of the Basis in the Simplex Method.- Partial Differential Equations.- A New Iterative Procedure for the Solution of Sparse Systems of Linear Difference Equations.- Block Eliminations on Finite Element Systems of Equations.- Application of the Finite Element Method to Regional Water Transport Phenomena.- On the Use of Fast Methods for Separable Finite Difference Equations for the Solution of General Elliptic Problems.- Special Topics.- Application of Sparse Matrices to Analytical Photogrammetry.- Generalized View of a Data Base.- Combinatorics and Graph Theory.- Several Strategies for Reducing the Bandwidth of Matrices.- GRAAL A Graph Algorithmic Language.- The Role of Partitioning in the Numerical Solution of Sparse Systems.