Muutke küpsiste eelistusi

E-raamat: Fundamentals of Matrix Analysis with Applications

  • Formaat: EPUB+DRM
  • Ilmumisaeg: 12-Oct-2015
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118953693
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 121,65 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 12-Oct-2015
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118953693
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

An accessible and clear introduction to linear algebra with a focus on matrices and engineering applications

Providing comprehensive coverage of matrix theory from a geometric and physical perspective, Fundamentals of Matrix Analysis with Applications describes the functionality of matrices and their ability to quantify and analyze many practical applications. Written by a highly qualified author team, the book presents tools for matrix analysis and is illustrated with extensive examples and software implementations.

Beginning with a detailed exposition and review of the Gauss elimination method, the authors maintain readers interest with refreshing discussions regarding the issues of operation counts, computer speed and precision, complex arithmetic formulations, parameterization of solutions, and the logical traps that dictate strict adherence to Gausss instructions. The book heralds matrix formulation both as notational shorthand and as a quantifier of physical operations such as rotations, projections, reflections, and the Gauss reductions. Inverses and eigenvectors are visualized first in an operator context before being addressed computationally. Least squares theory is expounded in all its manifestations including optimization, orthogonality, computational accuracy, and even function theory. Fundamentals of Matrix Analysis with Applications also features:





Novel approaches employed to explicate the QR, singular value, Schur, and Jordan decompositions and their applications Coverage of the role of the matrix exponential in the solution of linear systems of differential equations with constant coefficients Chapter-by-chapter summaries, review problems, technical writing exercises, select solutions, and group projects to aid comprehension of the presented concepts

Fundamentals of Matrix Analysis with Applications is an excellent textbook for undergraduate courses in linear algebra and matrix theory for students majoring in mathematics, engineering, and science. The book is also an accessible go-to reference for readers seeking clarification of the fine points of kinematics, circuit theory, control theory, computational statistics, and numerical algorithms.

 

Arvustused

"Providing comprehensive coverage of matrix theory from a geometric and physical perspective, the book describes the functionality of matrices and their ability to quantify and analyze many practical applications. Written by a highly qualified author team, the book presents tools for matrix analysis and is illustrated with extensive examples and software implementations." (Zentralblatt MATH 2016).

"This is a straightforward modern introduction to matrices..... a very well done text, probably most suitable for engineering students." (Mathematical Association of America 2016).

Preface ix
PART I INTRODUCTION: THREE EXAMPLES
1(115)
1 Systems of Linear Algebraic Equations
5(53)
1.1 Linear Algebraic Equations
5(12)
1.2 Matrix Representation of Linear Systems and the Gauss-Jordan Algorithm
17(10)
1.3 The Complete Gauss Elimination Algorithm
27(11)
1.4 Echelon Form and Rank
38(8)
1.5 Computational Considerations
46(9)
1.6 Summary
55(3)
2 Matrix Algebra
58(58)
2.1 Matrix Multiplication
58(11)
2.2 Some Physical Applications of Matrix Operators
69(7)
2.3 The Inverse and the Transpose
76(10)
2.4 Determinants
86(14)
2.5 Three Important Determinant Rules
100(11)
2.6 Summary
111(5)
Group Projects for Part I
A LU Factorization
116(2)
B Two-Point Boundary Value Problem
118(1)
C Electrostatic Voltage
119(1)
D Kirchhoff's Laws
120(2)
E Global Positioning Systems
122(1)
F Fixed-Point Methods
123(6)
PART II INTRODUCTION: THE STRUCTURE OF GENERAL SOLUTIONS TO LINEAR ALGEBRAIC EQUATIONS
129(72)
3 Vector Spaces
133(32)
3.1 General Spaces, Subspaces, and Spans
133(9)
3.2 Linear Dependence
142(9)
3.3 Bases, Dimension, and Rank
151(13)
3.4 Summary
164(1)
4 Orthogonality
165(36)
4.1 Orthogonal Vectors and the Gram-Schmidt Algorithm
165(9)
4.2 Orthogonal Matrices
174(6)
4.3 Least Squares
180(10)
4.4 Function Spaces
190(7)
4.5 Summary
197(4)
Group Projects for Part II
A Rotations and Reflections
201(1)
B Householder Reflectors
201(1)
C Infinite Dimensional Matrices
202(3)
PART III INTRODUCTION: REFLECT ON THIS
205(137)
5 Eigenvectors and Eigenvalues
209(24)
5.1 Eigenvector Basics
209(8)
5.2 Calculating Eigenvalues and Eigenvectors
217(8)
5.3 Symmetric and Hermitian Matrices
225(7)
5.4 Summary
232(1)
6 Similarity
233(60)
6.1 Similarity Transformations and Diagonalizability
233(11)
6.2 Principle Axes and Normal Modes
244(13)
6.3 Schur Decomposition and Its Implications
257(7)
6.4 The Singular Value Decomposition
264(18)
6.5 The Power Method and the QR Algorithm
282(8)
6.6 Summary
290(3)
7 Linear Systems of Differential Equations
293(49)
7.1 First-Order Linear Systems
293(13)
7.2 The Matrix Exponential Function
306(10)
7.3 The Jordan Normal Form
316(17)
7.4 Matrix Exponentiation via Generalized Eigenvectors
333(6)
7.5 Summary
339(3)
Group Projects for Part III
A Positive Definite Matrices
342(1)
B Hessenberg Form
343(1)
C Discrete Fourier Transform
344(2)
D Construction of the SVD
346(2)
E Total Least Squares
348(2)
F Fibonacci Numbers
350(1)
Answers To Odd Numbered Exercises 351(42)
Index 393
EDWARD BARRY SAFF, PhD, is Professor of Mathematics and Director of the Center for Constructive Approximation at Vanderbilt University. Dr. Saff is an Inaugural Fellow of the American Mathematical Society, Foreign Member of the Bulgarian Academy of Science, and the recipient of both a Guggenheim and Fulbright Fellowship. He is Editor-in-Chief of two research journals, Constructive Approximation and Computational Methods and Function Theory, and has authored or coauthored over 250 journal articles and eight books. Dr. Saff also serves as an organizer for a sequence of international research conferences that help to foster the careers of mathematicians from developing countries.

ARTHUR DAVID SNIDER, PhD, PE, is Professor Emeritus at the University of South Florida, where he served on the faculties of the Departments of Mathematics, Physics, and Electrical Engineering. Previously an analyst at the Massachusetts Institute of Technology's Draper Lab and recipient of the USF Krivanek Distinguished Teacher Award, he consults in industry and has authored or coauthored over 100 journal articles and eight books. With the support of the National Science Foundation, Dr. Snider also pioneered a course in fine art appreciation for engineers.