3 edition of **Minimax models in the theory of numerical methods** found in the catalog.

Minimax models in the theory of numerical methods

A. G. Sukharev

- 380 Want to read
- 2 Currently reading

Published
**1992**
by Kluwer Academic Publishers in Dordrecht, Boston
.

Written in English

- Numerical analysis,
- Maxima and minima

**Edition Notes**

Statement | Aleksei G. Sukharev. |

Series | Theory and decision library., v. 21 |

Classifications | |
---|---|

LC Classifications | QA300 .S9613 1992 |

The Physical Object | |

Pagination | xiv, 256 p. ; |

Number of Pages | 256 |

ID Numbers | |

Open Library | OL1714291M |

ISBN 10 | 0792318218 |

LC Control Number | 92016531 |

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In the Russian edition published inthis book was called "Minimax Algorithms in Problems of Numerical Analysis". The new title is better related to the subject of the book and its style. The basis for every decision or inference concerning the ways to solve a given problem is the computa tion model.

Additional Physical Format: Online version: Sukharev, A.G. (Alekseĭ Grigorʹevich). Minimax models in the theory of numerical methods. Dordrecht ; Boston: Kluwer. In Minimax Models in the Theory of Numerical Methods, methods for estimating the efficiency of computational algorithms and problems of their optimality are studied within the framework of a general computation model.

The subjects dealt with in this important book are very different from the traditional subjects of computational methods. (ebook) Minimax Models in the Theory of Numerical Methods () from Dymocks online store.

In the Russian edition published inthis book was. Australia’s leading bookseller for years. Minimax Methods in Critical Point Theory with Applications to Differential Equations (Cbms Regional Conference Series in Mathematics) Find all the books Cited by: Based on the local theory, a new local numerical minimax method for finding multiple saddle points is developed.

The local theory is applied, and the numerical method is implemented successfully to solve a class of semilinear elliptic boundary value problems for multiple solutions on some nonconvex, non star-shaped and multiconnected by: This international journal is entirely devoted to the mathematical applications of minimax results, methods and techniques (understood in the broadest and inclusive sense) to topics from optimization theory, calculus of variations, mathematical programming, game theory, control theory, convex analysis.

Game Theory: Models, Numerical Methods and Applications Abstract: This monograph provides the reader with a comprehensive overview of game theory covering the foundations of the theory of noncooperative and cooperative games, both static and by: 3. Endorsements.

Judd's book is a masterpiece which will help transform the way economic theory is done. It harnesses the computer revolution in the service of economic theory by collecting together a whole array of numerical methods to simulate and quantify models that used to be purely algebraic and qualitative.

Mathematical Methods in Engineering and Science Operational Fundamentals of Linear Alge Range and Null Space: Rank and Nullity Basis Change of Basis Elementary Transformations. Range and Null Space: Rank and Nullity. Consider A ∈Rm×n as a mapping A: Rn →Rm, Ax = y, x ∈Rn, y ∈ Size: 2MB.

Stochastic Programming: Minimax Approach. Anandalingam G () A stochastic programming process model for investment planning. Gaivoronski A () A numerical method for solving stochastic programming problems with moment constraints on a. A numerical method for determining a linear minimax estimator in the linear regression model with restricted parameter space is developed, and some numerical results are presented.

A Numerical Method for an Approximate Minimax Estimator in Linear Regression Jg Lauterbach and Peter Stahlecker Univer-sWit Oldenburg Institut fir Cited by: 4. Numerical Methods for Partial Differential Equations() A smooth method for the finite minimax problem.

Mathematical ProgrammingCited by: In this paper, we proposed a smoothing iterative method to solve the finite minimax problems based on the exponential penalty function of Kort and Bertsekas (). This approach can be viewed as the extension of one conjugate gradient method.

Under suitable conditions, the proposed method is globally : J.K. Liu, L. Zheng. A general method is described for the numerical evaluation of integrals of the form where, in a typical case, Φ(x, y) is a lengthy polynomial of degree≥ 10 in (x, y) and A is the region common.

For example, numerical parameterizations of the model using optimization methods would likely only yield one solution to the problem; this solution would be dependent upon the numerical method.

Minimax Theory 0 Comments Game theory Minimax Algorithm in Game Theory | Set 4 (Alpha-Beta Social Contract Theory in a Global Marketing Context Book review | Beautiful Game Theory: How Soccer can Help Game theory - Wikipedia ゲームのアルゴリズム ミニマックス法とアルファベータ法 - NAVER まとめ.

Judd's book is a masterpiece which will help transform the way economic theory is done. It harnesses the computer revolution in the service of economic theory by collecting together a whole array of numerical methods to simulate and quantify models that used to be purely algebraic and qualitative.

―Avinash K. Dixit, Princeton UniversityCited by: Part I: Decision Theory – Concepts and Methods 5 dependent on θ, as stated above, is denoted as)Pθ(E or)Pθ(X ∈E where E is an event. It should also be noted that the random variable X can be assumed to be either continuous or discrete.

Although, both cases are described here, the majority of this report focuses. Methods are described for the derivation of minimax and near-minimax polynomial approximations.

For minimax approximations techniques are considered for both analytically defined functions and functions defined by a table of by:. In linear algebra and functional analysis, the min-max theorem, or variational theorem, or Courant–Fischer–Weyl min-max principle, is a result that gives a variational characterization of eigenvalues of compact Hermitian operators on Hilbert can be viewed as the starting point of many results of similar nature.

This article first discusses the finite-dimensional case .Minimax (sometimes MinMax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, game theory, statistics, and philosophy for minimizing the possible loss for a worst case (maximum loss) dealing with gains, it is referred to as "maximin"—to maximize the minimum gain.

Originally formulated for two-player zero-sum game theory. Numerical Analysis - Theory and Application is an edited book divided into two parts: Part I devoted to Theory, and Part II dealing with Application. The presented book is focused on introducing theoretical approaches of numerical analysis as well as applications of various numerical methods to either study or solving numerous theoretical and engineering Cited by: