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Matrix, Numerical, and Optimization Methods HARDCOVER 2021 by Kevin W. Cassel

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Objectstaat
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Een boek dat slijtage vertoont. De kaft kan enigszins beschadigd zijn, maar is als geheel nog intact. De boekband kan licht beschadigd zijn, maar is als geheel nog intact. Er kan in de kantlijn zijn geschreven. Er kan tekst zijn onderstreept of gemarkeerd, maar er ontbreken geen bladzijden of iets anders waardoor de tekst minder goed leesbaar of minder begrijpelijk wordt. Bekijk de aanbieding van de verkoper voor de volledige details en een beschrijving van gebreken. Alle staatdefinities bekijkenwordt in nieuw venster of op nieuw tabblad geopend
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ISBN
110847909X
Book Title
name
Subject Area
Technology & Engineering, Mathematics
Publication Name
Matrix, Numerical, and Optimization Methods in Science and Engineering
Publisher
Cambridge University Press
Item Length
9.1 in
Subject
Engineering (General), General
Publication Year
2021
Type
Textbook
Format
Hardcover
Language
English
Item Height
1.8 in
Author
Kevin W. Cassel
Item Weight
47.6 Oz
Item Width
5.9 in
Number of Pages
600 Pages

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Product Information

Address vector and matrix methods necessary in numerical methods and optimization of linear systems in engineering with this unified text. Treats the mathematical models that describe and predict the evolution of our processes and systems, and the numerical methods required to obtain approximate solutions. Explores the dynamical systems theory used to describe and characterize system behaviour, alongside the techniques used to optimize their performance. Integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. Consolidating, generalizing, and unifying these topics into a single coherent subject, this practical resource is suitable for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
110847909x
ISBN-13
9781108479097
eBay Product ID (ePID)
3050094094

Product Key Features

Number of Pages
600 Pages
Language
English
Publication Name
Matrix, Numerical, and Optimization Methods in Science and Engineering
Publication Year
2021
Subject
Engineering (General), General
Type
Textbook
Subject Area
Technology & Engineering, Mathematics
Author
Kevin W. Cassel
Format
Hardcover

Dimensions

Item Height
1.8 in
Item Weight
47.6 Oz
Item Length
9.1 in
Item Width
5.9 in

Additional Product Features

LCCN
2020-022768
Dewey Edition
23
Reviews
'In this well-written reader friendly book, Professor Cassel systematically presents a wide range of mathematical concepts and methods, including matrix, numerical, and optimization methods, that are crucial in science and engineering. In particular, the book treats the mathematical models that describe and predict the evolution of various processes and systems, and the numerical methods required to obtain approximate solutions. It also explores the dynamical systems theory used to describe and characterize system behavior, alongside the techniques used to optimize their performance. The book integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. This book is a valuable reference or textbook for advanced undergraduate and graduate students in engineering, physical sciences, and applied mathematics.' Zhongshan Li, Georgia State University
Target Audience
Scholarly & Professional
Illustrated
Yes
Dewey Decimal
512.9434
Lc Classification Number
Qa188.C37 2021
Table of Content
Part I. Matrix Methods: 1. Vector and matrix algebra; 2. Algebraic eigenproblems and their applications; 3. Differential eigenproblems and their applications; 4. Vector and matrix calculus; 5. Analysis of discrete dynamical systems; Part II. Numerical Methods: 6. Computational linear algebra; 7. Numerical methods for differential equations; 8. Finite-difference methods for boundary-value problems; 9. Finite-difference methods for initial-value problems; Part III. Least Squares and Optimization: 10. Least-squares methods; 11. Data analysis - curve fitting and interpolation; 12. Optimization and root finding of algebraic systems; 13. Data-driven methods and reduced-order modeling.

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