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Elements of the General Theory of Op...
~
Lytvyn, Oleg M.
Elements of the General Theory of Optimal Algorithms
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Elements of the General Theory of Optimal Algorithms/ by Ivan V. Sergienko, Valeriy K. Zadiraka, Oleg M. Lytvyn.
Author:
Sergienko, Ivan V.
other author:
Zadiraka, Valeriy K.
Description:
XVII, 378 p. 9 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Mathematics—Data processing. -
Online resource:
https://doi.org/10.1007/978-3-030-90908-6
ISBN:
9783030909086
Elements of the General Theory of Optimal Algorithms
Sergienko, Ivan V.
Elements of the General Theory of Optimal Algorithms
[electronic resource] /by Ivan V. Sergienko, Valeriy K. Zadiraka, Oleg M. Lytvyn. - 1st ed. 2021. - XVII, 378 p. 9 illus.online resource. - Springer Optimization and Its Applications,1881931-6836 ;. - Springer Optimization and Its Applications,104.
-Preface -- Introduction -- List of symbols and abbreviations -- 1. Elements of the computing theory -- 2. Theories of computational complexity -- 3. Interlination of functions -- 4. Interflatation of functions -- 5. Cubature formulae using interlanation functions -- 6. Testing the quality of algorithm programs -- 7. Computer technologies of solving problems of computational and applied mathematics with fixed values of quality characteristics -- Bilbiography -- Index -- About the Authors.
In this monograph, the authors develop a methodology that allows one to construct and substantiate optimal and suboptimal algorithms to solve problems in computational and applied mathematics. Throughout the book, the authors explore well-known and proposed algorithms with a view toward analyzing their quality and the range of their efficiency. The concept of the approach taken is based on several theories (of computations, of optimal algorithms, of interpolation, interlination, and interflatation of functions, to name several). Theoretical principles and practical aspects of testing the quality of algorithms and applied software, are a major component of the exposition. The computer technology in construction of T-efficient algorithms for computing ε-solutions to problems of computational and applied mathematics, is also explored. The readership for this monograph is aimed at scientists, postgraduate students, advanced students, and specialists dealing with issues of developing algorithmic and software support for the solution of problems of computational and applied mathematics.
ISBN: 9783030909086
Standard No.: 10.1007/978-3-030-90908-6doiSubjects--Topical Terms:
1365953
Mathematics—Data processing.
LC Class. No.: QA71-90
Dewey Class. No.: 518
Elements of the General Theory of Optimal Algorithms
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-Preface -- Introduction -- List of symbols and abbreviations -- 1. Elements of the computing theory -- 2. Theories of computational complexity -- 3. Interlination of functions -- 4. Interflatation of functions -- 5. Cubature formulae using interlanation functions -- 6. Testing the quality of algorithm programs -- 7. Computer technologies of solving problems of computational and applied mathematics with fixed values of quality characteristics -- Bilbiography -- Index -- About the Authors.
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In this monograph, the authors develop a methodology that allows one to construct and substantiate optimal and suboptimal algorithms to solve problems in computational and applied mathematics. Throughout the book, the authors explore well-known and proposed algorithms with a view toward analyzing their quality and the range of their efficiency. The concept of the approach taken is based on several theories (of computations, of optimal algorithms, of interpolation, interlination, and interflatation of functions, to name several). Theoretical principles and practical aspects of testing the quality of algorithms and applied software, are a major component of the exposition. The computer technology in construction of T-efficient algorithms for computing ε-solutions to problems of computational and applied mathematics, is also explored. The readership for this monograph is aimed at scientists, postgraduate students, advanced students, and specialists dealing with issues of developing algorithmic and software support for the solution of problems of computational and applied mathematics.
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