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Solving Least Squares Problems
This Classic edition includes a new appendix which summarizes the major developments since the book was originally published in 1974. The additions are organized in short sections associated with each chapter. An additional 230 references have been added, bringing the bibliography to over 400 entries. Appendix C has been edited to reflect changes in the associated software package and software distribution method.
Perturbations
This book gives a thorough introduction to both regular and singular perturbation methods for algebraic and differential equations.
The Finite Element Method for Elliptic Problems
This is the only book available that fully analyzes the mathematical foundations of the finite element method. Not only is it valuable reference and introduction to current research, it is also a working textbook for graduate courses in numerical analysis, including useful figures and exercises of varying difficulty.
Normal Approximation and Asymptotic Expansions
-Fourier analysis, --
Stochastic Systems
Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.
Principles of Computerized Tomographic Imaging
Principles of Computerized Tomographic Imaging provides a comprehensive, tutorial-style introduction to the algorithms for reconstructing cross-sectional images from projection data and contains a complete overview of the engineering and signal processing algorithms necessary for tomographic imaging. In addition to the purely mathematical and algorithmic aspects of these algorithms, the book also discusses the artifacts caused by the nature of the various forms of energy sources that can be used for generating the projection data. Since the fundamental aspects of tomographic reconstruction algorithms have remained virtually the same since this book was originally published, it is just as useful today as it was in 1987. It explains, among other things, what happens when there is excessive noise in the projection data; when images are formed from insufficient projection data; and when refracting or diffracting energy sources are used for imaging. Audience: beginning graduate students or practitioners wishing to see the development of the algorithm from the ground up, as well as anyone interested in cross-sectional imaging for a wide variety of applications.
Biennial Report
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