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Practical Linear Algebra: A Geometry Toolbox de Gerald Farin

Practical Linear Algebra: A Geometry Toolbox: Textbooks in Mathematics

Autor Gerald Farin, Dianne Hansford
en Limba Engleză Paperback – 26 aug 2024

Structura volumului Practical Linear Algebra este construită pe o metodologie progresivă care prioritizează intuiția vizuală în detrimentul abstractizării timpurii. Suntem de părere că decizia autorilor de a ancora primele capitole în spațiile 2D și 3D este esențială pentru studenții care au nevoie de o bază solidă în modelarea geometrică. Materialul este organizat riguros, începând cu sistemele de coordonate Descartes și vectorii plani, progresând natural către transformări liniare, spații vectoriale și, în final, către dimensiuni superioare și structuri complexe. Notăm cu interes modul în care această a patra ediție rafinează conceptele de schimbare a bazei și diagonalizare, oferind o claritate sporită asupra spațiilor nucleu (kernel).

În contextul operei lor, Practical Linear Algebra reprezintă o extensie firească a preocupărilor explorate în The Essentials of CAGD sau Geometric Modelling. Dacă lucrările anterioare se concentrau pe designul geometric asistat de calculator, volumul de față oferă fundamentul matematic necesar pentru acele aplicații. Găsim în acest text o punte între rigoarea teoretică și nevoile practice din industria divertismentului 3D și a științei datelor. Cartea completează perspectiva oferită de Linear Algebra de John B. Fraleigh, adăugând o componentă vizuală și algoritmică mult mai pronunțată, specifică ingineriei și graficii pe calculator. Spre deosebire de abordarea lui Fraleigh, care rămâne fidelă stilului clasic de curs universitar, Farin și Hansford transformă algebra într-o „cutie cu unelte” geometrice, facilitând înțelegerea prin cele peste 600 de ilustrații care însoțesc demonstrațiile.

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Specificații

ISBN-13: 9781032021911
ISBN-10: 1032021918
Pagini: 590
Ilustrații: 638
Dimensiuni: 191 x 235 x 36 mm
Greutate: 1.06 kg
Ediția:4th edition
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Textbooks in Mathematics

Locul publicării:Boca Raton, United States

Public țintă

Undergraduate Advanced

De ce să citești această carte

Această ediție este ideală pentru studenții de la facultățile de matematică, inginerie sau informatică care doresc să înțeleagă mecanismele din spatele graficii 3D și a algoritmilor moderni. Cititorul câștigă o viziune aplicată asupra algebrei liniare, învățând nu doar să rezolve ecuații, ci să vizualizeze transformările matematice. Este un instrument indispensabil pentru cei care vizează o carieră în animație, dezvoltare de jocuri sau analiza datelor masive.

Despre autor

Gerald Farin și Dianne Hansford sunt experți recunoscuți în design geometric și modelare pe calculator. Gerald Farin a fost o figură centrală în domeniul Computer-Aided Geometric Design (CAGD), contribuind semnificativ la dezvoltarea algoritmilor pentru curbe și suprafețe. Experiența lor academică și de cercetare se reflectă în capacitatea de a traduce concepte matematice aride în aplicații vizuale intuitive. Prin lucrările lor, au reușit să simplifice bagajul matematic necesar inginerilor și programatorilor, punând accent pe interpretarea geometrică și implementarea algoritmică a teoriei.

Cuprins

1. Descartes' Discovery. 1.1. Local and Global Coordinates: 2D. 1.2. Going from Global to Local. 1.3. Local and Global Coordinates: 3D. 1.4. Stepping Outside the Box. 1.5. Application: Creating Coordinates. 1.6. Exercises. 2. Here and There: Points and Vectors in 2D. 2.1. Points and Vectors. 2.2. What's the Difference? 2.3. Vector Fields. 2.4. Length of a Vector. 2.5. Combining Points. 2.6. Independence. 2.7. Dot Product. 2.8. Application: Lighting Model. 2.9. Orthogonal Projections. 2.10. Inequalities. 2.11. Exercises. 3. Lining Up: 2D Lines. 3.1. Defining a Line. 3.2. Parametric Equation of a Line. 3.3. Implicit Equation of a Line. 3.4. Explicit Equation of a Line. 3.5. Converting Between Line Forms. 3.6. Distance of a Point to a Line. 3.7. The Foot of a Point. 3.8. A Meeting Place: Computing Intersections. 3.9. Application: Closest Point of Approach. 3.10. Exercises. 4. Changing Shapes: Linear Maps in 2D. 4.1. Skew Target Boxes. 4.2. The Matrix Form. 4.3. Linear Spaces. 4.4. Scalings. 4.5 Reflections. 4.6. Rotations. 4.7. Shears. 4.8. Projections. 4.9. Application: Free-form Deformations. 4.10. Areas and Linear Maps: Determinants. 4.11. Composing Linear Maps. 4.12. More on Matrix Multiplication. 4.13. Matrix Arithmetic Rules. 4.14. Exercises. 5. 2 x 2 Linear Systems. 5.1. Skew Target Boxes Revisited. 5.2. The Matrix Form. 5.3. A Direct Approach: Cramer's Rule. 5.4. Gauss Elimination. 5.5. Pivoting. 5.6. Unsolvable Systems. 5.7. Underdetermined Systems. 5.8. Homogeneous Systems. 5.9. Kernel. 5.10. Undoing Maps: Inverse Matrices. 5.11. Defining a Map. 5.12. Change of Basis. 5.13. Application: Intersecting Lines. 5.14. Exercises. 6. Moving Things Around: Affine Maps in 2D. 6.1. Coordinate Transformations. 6.2. Affine and Linear Maps. 6.3. Translations. 6.4. Application: Animation. 6.5. Mapping Triangles to Triangles. 6.6. Composing Affine Maps. 6.7. Exercises. 7. Eigen Things. 7.1. Fixed Directions. 7.2. Eigenvalues. 7.3. Eigenvectors. 7.4. Striving for More Generality. 7.5. The Geometry of Symmetric Matrices and the Eigendecomposition. 7.6. Quadratic Forms. 7.7. Repeating Maps. 7.8. Exercises. 8. 3D Geometry. 8.1. From 2D to 3D. 8.2. Cross Product. 8.3. Lines. 8.4. Planes. 8.5. Scalar Triple Product. 8.6. Application: Lighting and Shading. 8.7. Exercises. 9. Linear Maps in 3D. 9.1. Matrices and Linear Maps. 9.2. Linear Spaces. 9.3. Scalings. 9.4. Reflections. 9.5 Shears. 9.6. Rotations. 9.7. Projections. 9.8. Volumes and Linear Maps: Determinants. 9.9. Combining Linear Maps. 9.10. Inverse Matrices. 9.11. Application: Mapping Normals. 9.12. More on Matrices. 9.13. Exercises. 10. Affine Maps in 3D. 10.1. Affine Maps. 10.2. Translations. 10.3. Mapping Tetrahedra. 10.4. Parallel Projections. 10.5. Homogeneous Coordinates and Perspective Maps. 10.6. Application: Building Instance Models. 10.7. Exercises. 11. Interactions in 3D. 11.1. Distance Between a Point and a Plane. 11.2. Distance Between Two Lines. 11.3. Lines and Planes: Intersections. 11.4. Intersecting a Triangle and a Line. 11.5. Reflections. 11.6. Intersecting Three Planes. 11.7. Intersecting Two Planes. 11.8. Creating Orthonormal Coordinate Systems. 11.9. Application: Camera Model. 11.10. Exercises. 12. Gauss for Linear Systems. 12.1. The Problem. 12.2. The Solution via Gauss Elimination. 12.3. Homogeneous Linear Systems. 12.4. Inverse Matrices. 12.5. LU Decomposition. 12.6. Determinants. 12.7. Least Squares. 12.8. Application: Fitting Data from a Femoral Head. 12.9. Exercises. 13. Alternative System Solvers. 13.1. The Householder Method. 13.2. Vector Norms. 13.3. Matrix Norms. 13.4. The Condition Number. 13.5. Vector Sequences. 13.6. Iterative Methods: Gauss-Jacobi and Gauss-Seidel. 13.7. Application: Mesh Smoothing. 13.8. Exercises. 14. General Linear Spaces. 14.1. Basic Properties of Linear Spaces. 14.2. Linear Maps. 14.3. Inner Products. 14.4. Gram-Schmidt Orthonormalization. 14.5. QR Decompositon. 14.6. A Gallery of Spaces. 14.7. Least Squares. 14.8. Application: Music Analysis. 14.9. Exercises. 15. Eigen Things Revisited. 15.1. The Basics Revisited. 15.2. Similarity and Diagonalization. 15.3. Quadratic Forms. 15.4. The Power Method. 15.5. Application: Google Eigenvector. 15.6. QR Algorithm. 15.7. Eigenfunctions. 15.8. Application: Inuenza Modelling. 15.9. Exercises. 16. The Singular Value Decomposition. 16.1. The Geometry of the 2 x 2 Case. 16.2. The General Case. 16.3. SVD Steps. 16.4. Singular Values and Volumes. 16.5. The Pseudoinverse. 16.6. Least Squares. 16.7. Application: Image Compression. 16.8. Principal Components Analysis. 16.9. Application: Face Authentication. 16.10. Exercises. 17. Breaking It Up: Triangles. 17.1. Barycentric Coordinates. 17.2. Affine Invariance. 17.3. Some Special Points. 17.4. 2D Triangulations. 17.5. A Data Structure. 17.6. Application: Point Location. 17.7. 3D Triangulations. 17.8. Exercises. 18. Putting Lines Together: Polylines and Polygons. 18.1 Polylines. 18.2. Polygons. 18.3. Convexity. 18.4. Types of Polygons. 18.5. Unusual Polygons. 18.6. Turning Angles and Winding Numbers. 18.7. Area. 18.8. Application: Planarity Test. 18.9. Application: Inside or Outside? 18.10. Exercises. 19. Conics. 19.1. The General Conic. 19.2. Analyzing Conics. 19.3. General Conic to Standard Position. 19.4. The Action Ellipse. 19.5. Exercises. 20. Curves. 20.1. Parametric Curves. 20.2. Properties of Bézier Curves. 20.3. The Matrix Form. 20.4. Derivatives. 20.5. Composite Curves. 20.6. The Geometry of Planar Curves. 20.7. Application: Moving along a Curve. 20.8. Exercises. A. Applications. B. Glossary. C. Selected Exercises Solutions. Bibliography.

Notă biografică

Gerald Farin (deceased) was a professor in the School of Computing, Informatics, and Design Systems Engineering (CIDSE) at Arizona State University. He received his doctoral degree in mathematics from the University of Braunschweig, Germany. His extensive experience in geometric design started at Daimler-Benz. He was a founding member of the editorial board for the journal Computer-Aided Geometric Design (Elsevier), and he served as co-editor in chief for more than 20 years. He published more than 100 research papers. Gerald also organized numerous conferences and authored or edited 29 books. This includes his much read and referenced textbook Curves and Surfaces for CAGD and his book on NURBS. In addition to this book, Gerald and Dianne co-authored The Essentials of CAGD, Mathematical Principles for Scientific Computing and Visualization both also published by AK Peters/CRC Press.
Dianne Hansford, received her Ph.D. from Arizona State University. Her research interests are in the field of geometric modeling with a focus on industrial curve and surface applications related to mathematical definitions of shape. Together with Gerald Farin (deceased), she delivered custom software solutions, advisement on best practices, and taught on-site courses as a consultant. She is a co-founder of 3D Compression Technologies. She is now lecturer in the School of Computing, Informatics, and Design Systems Engineering (CIDSE) at Arizona State University, primarily teaching geometric design, computer graphics, and scientific computing and visualization. In addition to this book, Gerald and Dianne co-authored The Essentials of CAGD, Mathematical Principles for Scientific Computing and Visualization both also published by AK Peters/CRC Press.

Descriere scurtă

Linear algebra is growing in importance. 3D entertainment, animations in movies and video games are developed using linear algebra. Animated characters are generated using equations straight out of this book. Linear algebra is used to extract knowledge from the massive amounts of data generated from modern technology.
The Fourth Edition of this popular text introduces linear algebra in a comprehensive, geometric, and algorithmic way. The authors start with the fundamentals in 2D and 3D, then move on to higher dimensions, expanding on the fundamentals and introducing new topics, which are necessary for many real-life applications and the development of abstract thought. Applications are introduced to motivate topics.
The subtitle, A Geometry Toolbox, hints at the book’s geometric approach, which is supported by many sketches and figures. Furthermore, the book covers applications of triangles, polygons, conics, and curves. Examples demonstrate each topic in action.
This practical approach to a linear algebra course, whether through classroom instruction or self-study, is unique to this book.
New to the Fourth Edition:
  • Ten new application sections
  • A new section on change of basis. This concept now appears in several places
  • Chapters 14-16 on higher dimensions are notably revised
  • A deeper look at polynomials in the gallery of spaces
  • Introduces the QR decomposition and its relevance to least squares
  • Similarity and diagonalization are given more attention, as are eigenfunctions
  • A longer thread on least squares, running from orthogonal projections to a solution via SVD and the pseudoinverse
  • More applications for PCA have been added
  • More examples, exercises, and more on the kernel and general linear spaces
  • A list of applications has been added in Appendix A
The book gives instructors the option of tailoring the course for the primary interests of their students: mathematics, engineering, science, computer graphics, and geometric modeling.