Complexity and Information

Häftad, Engelska, 1998

Av J. F. Traub, A. G. Werschulz, New York) Traub, J. F. (Columbia University, New York) Werschulz, A. G. (Fordham University and Columbia University, J. Traub, Arthur G. Werschulz

779 kr

Beställningsvara. Skickas inom 7-10 vardagar

Fri frakt för medlemmar vid köp för minst 249 kr.

The twin themes of computational complexity and information pervade this 1998 book. It starts with an introduction to the computational complexity of continuous mathematical models, that is, information-based complexity. This is then used to illustrate a variety of topics, including breaking the curse of dimensionality, complexity of path integration, solvability of ill-posed problems, the value of information in computation, assigning values to mathematical hypotheses, and new, improved methods for mathematical finance. The style is informal, and the goals are exposition, insight and motivation. A comprehensive bibliography is provided, to which readers are referred for precise statements of results and their proofs. As the first introductory book on the subject it will be invaluable as a guide to the area for the many students and researchers whose disciplines, ranging from physics to finance, are influenced by the computational complexity of continuous problems.

Produktinformation

Utgivningsdatum1998-12-10
Mått140 x 216 x 9 mm
Vikt200 g
FormatHäftad
SpråkEngelska
SerieLezioni Lincee
Antal sidor154
FörlagCambridge University Press
ISBN9780521485067

Tillhör följande kategorier

Part I. Fundamentals: 1. Introduction; 2. Information-based complexity; 3. Breaking the curse of dimensionality; Part II. Some Interesting Topics: 4. Very high-dimensional integration and mathematical finance; 5. Complexity of path integration; 6. Are ill-posed problems solvable?; 7. Complexity of nonlinear problems; 8. What model of computation should be used by scientists?; 9. Do impossibility theorems from formal models limit scientific knowledge? 10. Complexity of linear programming; 11. Complexity of verification; 12. Complexity of implementation testing; 13. Noisy information; 14. Value of information in computation; 15. Assigning values to mathematical hypotheses; 16. Open problems; 17. A brief history of information-based complexity; Part III. References: 18. A guide to the literature; Bibliography; Subject index; Author index.