Scientific Computation

Inbunden, Engelska, 2009

864 kr

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Beskrivning

Using real-life applications, this graduate-level textbook introduces different mathematical methods of scientific computation to solve minimization problems using examples ranging from locating an aircraft, finding the best time to replace a computer, analyzing developments on the stock market, and constructing phylogenetic trees. The textbook focuses on several methods, including nonlinear least squares with confidence analysis, singular value decomposition, best basis, dynamic programming, linear programming, and various optimization procedures. Each chapter solves several realistic problems, introducing the modelling optimization techniques and simulation as required. This allows readers to see how the methods are put to use, making it easier to grasp the basic ideas. There are also worked examples, practical notes, and background materials to help the reader understand the topics covered. Interactive exercises are available at www.cambridge.org/9780521849890.

Produktinformation

Utgivningsdatum:2009-11-05
Mått:194 x 252 x 14 mm
Vikt:710 g
Format:Inbunden
Språk:Engelska
Antal sidor:250
Förlag:Cambridge University Press
ISBN:9780521849890

Utforska kategorier

Fysik inom Naturvetenskap och teknik

Mer om författaren

Gaston H. Gonnet is a Professor in the Department of Informatik at ETH, Zurich. His research interests lie in symbolic and algebraic computation, system development, limit and series computation and heuristic algorithms, computational biochemistry algorithms, and the design and analysis of algorithms. Ralf Scholl teaches mathematics, physics, and science and technology at the Geschwister-Scholl-Gymnasium in Stuttgart. His interests lie in the didactics of teaching science and mathematics at high school to graduate level.

Recensioner i media

'… this book will help students understand methods in some of their appropriate contexts, in a relatively easy, fresh, and concise way.' E. Vavalis, Computing Reviews

Innehållsförteckning

Preface; 1. Determination of the accurate location of an aircraft; 2. When to replace equipment; 3. SSP using LS and SVD; 4. SSP using least squares and best basis; 5. SSP learning methods (nearest neighbours); 6. SSP with linear programming (LP); 7. Stock market prediction; 8. Phylogenetic tree construction; Appendixes; Index.