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This expansive volume describes the history of numerical methods proposed for solving linear algebra problems, from antiquity to the present day. The authors focus on methods for linear systems of equations and eigenvalue problems and describe the interplay between numerical methods and the computing tools available at the time. The second part of the book consists of 78 biographies of important contributors to the field. A Journey through the History of Numerical Linear Algebra will be of special interest to applied mathematicians, especially researchers in numerical linear algebra, people involved in scientific computing, and historians of mathematics.
Winner of the Computer History Museum Prize of the Special Interest Group: Computers, Information, and Society Imagine biology and medicine today without computers. What would laboratory work be like if electronic databases and statistical software did not exist? Would disciplines like genomics even be feasible if we lacked the means to manage and manipulate huge volumes of digital data? How would patients fare in a world absent CT scans, programmable pacemakers, and computerized medical records? Today, computers are a critical component of almost all research in biology and medicine. Yet, just fifty years ago, the study of life was by far the least digitized field of science, its living sub...
An interrelated account of difference methods and results, thistext covers hyperbolic equations in two independent variables, parabolic and elliptic equations, and initial-value problems in more than two independent variables. 1960 edition."
A celebration of the women who furthered computer technology, from the nineteenth century to the present day.
First Published in 1996. Routledge is an imprint of Taylor & Francis, an informa company.
Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.
A probing examination of the dynamic history of predictive methods and values in science and engineering that helps us better understand today’s cultures of prediction. The ability to make reliable predictions based on robust and replicable methods is a defining feature of the scientific endeavor, allowing engineers to determine whether a building will stand up or where a cannonball will strike. Cultures of Prediction, which bridges history and philosophy, uncovers the dynamic history of prediction in science and engineering over four centuries. Ann Johnson and Johannes Lenhard identify four different cultures, or modes, of prediction in the history of science and engineering: rational, em...
Includes entries for maps and atlases.