Checking date: 14/05/2020


Course: 2019/2020

Linear Geometry
(18259)
Study: Bachelor in Applied Mathematics and Computing (362)


Coordinating teacher: SANZ SERNA, JESUS MARIA

Department assigned to the subject: Department of Mathematics

Type: Basic Core
ECTS Credits: 6.0 ECTS

Course:
Semester:

Branch of knowledge: Engineering and Architecture



Students are expected to have completed
Fundamentals of Algebra, Linear Algebra, Differential Calculus
Competences and skills that will be acquired and learning results. Further information on this link
1. Students have shown that they know and understand the mathematical language and the abstract-rigorous reasoning, as well as to apply them to state and prove precise results in several areas of mathematics. 2. Students have shown that they understand the fundamental results of linear algebra, matrix theory and linear geometry concerning spectral theory of matrices and linear transformations, symmetric and Hermitian matrices, affine spaces and projective geometry. 3. Students are able to use techniques from linear algebra, matrix theory and linear geometry to construct mathematical models of processes that appear in real world applications. 4. Students are able to communicate, in a precise and clear manner, ideas, problems and solutions related to linear algebra, matrix theory and linear geometry to any kind of audience (specialist or not).
Description of contents: programme
1. Eigenvalues and eigenvectors: diagonalization of matrices and Schur's triangularization 2. The Jordan canonical form 3. Normal matrices and their spectral theorem 4. Positive definite matrices 5. Bilinear and quadratic forms 6. The singular value decomposition 7. Affine spaces and their applications 8. Affine transformations 9. Projective geometry and its applications 10. Conic sections and quadric surfaces
Learning activities and methodology
1. THEORETICAL-PRACTICAL CLASSES, where the knowledge that the students must acquire is explained and developed. Students will have basic reference texts to facilitate the understanding of the classes and the development of follow up work. The teacher and the students will solve exercises and practical problems, previously suggested by the teacher. There will be mid term tests for evaluating the competences and skills acquired by the students and for helping the students to improve their learning strategies. 2. TUTORING SESSIONS. Individualized attendance for students with a teacher for at least two hours a week. 3. STUDENT INDIVIDUAL OR GROUP WORK. Each student's individualized study, understanding of results and proofs, and exercise and problem solving is fundamental in mathematics, both for learning and for self-evaluation of acquired competences and skills. Solving exercises and problems and discussing theoretical results inside small groups of students is an excellent complementary activity for improving the learning.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40
Basic Bibliography
  • C.D. Meyer. Matrix Analysis and Applied Linear Algebra. SIAM. 2000
  • D.C. Lay, S.R. Lay and J.J. McDonald. Linear Algebra and its Applications, 5th edition. Pearson. 2016
  • G. Strang. Introduction to Linear Algebra. Wellesley-Cambridge Press. 2016
  • O. Faugeras. Three Dimensional Computer Vision, A Geometric Viewpoint. The MIT Press. 1993
  • S.R. García and R.A. Horn. A Second Course in Linear Algebra. Cambridge University Press. 2017
Additional Bibliography
  • B. Noble and J.W. Daniel. Applied Linear Algebra. Prentice-Hall Int.. 1988
  • E. Outerelo Domínguez y J.M. Sánchez Abril. Nociones de Geometría Proyectiva. Sanz y Torres. 2009
  • P. Lancaster and M. Tismenetsky. The Theory of Matrices with Applications, 2nd edition. Academic Press, Inc.. 1985
  • R.A. Horn and C.R. Johnson. Matrix Analysis, 2nd edition. Cambridge University Press. 2013

The course syllabus and the academic weekly planning may change due academic events or other reasons.