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Matrix, Numerical, and Optimization Methods HARDCOVER 2021 by Kevin W. Cassel
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免費 USPS First Class®.
所在地：Hickory, North Carolina, 美國
送達日期：
估計於 9月28日, 六至 10月1日, 二之間送達 運送地點 43230
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物品細節
- 物品狀況
- 尚可
- 賣家備註
- ISBN
- 110847909X
- Book Title
- name
- Subject Area
- Mathematics, Technology & Engineering
- 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
- Item Weight
- 47.6 Oz
- Item Width
- 5.9 in
- Number of Pages
- 600 Pages
關於產品
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
Subject
Engineering (General), General
Publication Year
2021
Type
Textbook
Subject Area
Mathematics, Technology & Engineering
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
Intended Audience
Scholarly & Professional
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
Illustrated
Yes
Dewey Decimal
512.9434
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.
Synopsis
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., Address vector and matrix methods necessary in numerical methods and optimization of linear systems with this practical, unified text. Perfect for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.
LC Classification Number
QA188.C37 2021
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