Scientific computation / Gaston H. Gonnet, Ralf Scholl.Material type: TextPublication details: Cambridge, UK ; New York : Cambridge University Press, 2009. Description: 1 online resource (xii, 236 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9780511656293; 0511656297; 9780511658150; 051165815X; 9780511815027; 0511815026; 9780511656842; 051165684XSubject(s): Computer science -- Mathematics | Science -- Data processing | Data structures (Computer science) | Bioinformatics | SCIENCE -- Philosophy & Social Aspects | Bioinformatics | Computer science -- Mathematics | Data structures (Computer science) | Science -- Data processing | Wissenschaftliches Rechnen | Optimierung | Numerische Mathematik | Naturwissenschaften -- DatenverarbeitungGenre/Form: Electronic books. | Electronic books. Additional physical formats: Print version:: Scientific computation.DDC classification: 501/.51 LOC classification: QA76.9.M35 | G64 2009Other classification: ST 630 Online resources: Click here to access online
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"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 modeling 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."--Publisher's web site.
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.
Includes bibliographical references and index.