Course: Linear Algebra 2

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Course title Linear Algebra 2
Course code KAG/LA2M
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 6
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Jukl Marek, doc. RNDr. Ph.D.
  • Lachman Dominik, Mgr.
  • Vítková Lenka, Mgr. Ph.D.
Course content
1. Orthogonal projection, orthogonal homomorphism end isomorphism of euclidean vector space (isometry). 2. Factor vector space. 3. Dual vector space. 4. Endomorphisms, ring and linear algebra of endomorphisms. Similarity of square matrices. 5. Minimal and characteristic polynomials of endomorphism and matrix. 6. Invariant subspaces with respect to endomorphism. Vector subspaces associated with eigenvalues. 7. Root subspaces with respect to endomorphism. The Jordan basis, normal Jordan form of square matrices. 8. Ring of square polynomial matrices. Equivalency of polynomial matrices. 9. System of the greatest common divisors and system of invariant factors of a polynomial matrix, construction of the norma Jordan form of matrix. 10. Bilinear form on a vector space. 11. Quadratic form on a vector space. Polar bilinear form. 12. Conjugated vectors with respect to quadratic forms. Principal directions of quadratic forms in Euclidean vector space. 13. Signature of a quadratic form. Sylvester theorem and Sylvester criterion. 14. Generalised matrix inverse. Moore-Penrose homomorphism.

Learning activities and teaching methods
unspecified
Learning outcomes
1. Orthogonal projection, orthogonal homomorphism end isomorphism of euclidean vector space (isometry). 2. Factor vector space. 3. Dual vector space. 4. Endomorphisms, ring and linear algebra of endomorphisms. Similarity of square matrices. 5. Minimal and characteristic polynomials of endomorphism and matrix. 6. Invariant subspaces with respect to endomorphism. Vector subspaces associated with eigenvalues. 7. Root subspaces with respect to endomorphism. The Jordan basis, normal Jordan form of square matrices. 8. Ring of square polynomial matrices. Equivalency of polynomial matrices. 9. System of the greatest common divisors and system of invariant factors of a polynomial matrix, construction of the norma Jordan form of matrix. 10. Bilinear form on a vector space. 11. Quadratic form on a vector space. Polar bilinear form. 12. Conjugated vectors with respect to quadratic forms. Principal directions of quadratic forms in Euclidean vector space. 13. Signature of a quadratic form. Sylvester theorem and Sylvester criterion. 14. Generalised matrix inverse. Moore-Penrose homomorphism.

Prerequisites
unspecified
KAG/LA1A
----- or -----
KAG/LA1M

Assessment methods and criteria
unspecified
Recommended literature
  • Bican, L. (2009). Lineární algebra a geometrie. Praha.
  • Hefferon J. (2017). Linear algebra. Colchester.
  • Jukl, M. (2000). Bilineární a kvadratické formy. Olomouc.
  • Jukl, M. (2006). Lineární algebra. Euklidovské vektorové prostory Homomorfizmy vektorových prostorů. Olomouc.
  • Jukl, M. (2001). Lineární operátory. Olomouc.
  • Zlatoš, P. (2011). Lineárna algebra a geometria. Bratislava.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Data Science (2020) Category: Mathematics courses 1 Recommended year of study:1, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Industrial Mathematics (2020) Category: Mathematics courses 1 Recommended year of study:1, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Teaching Training in Mathematics for Secondary Schools (2019) Category: Pedagogy, teacher training and social care 1 Recommended year of study:1, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Mathematics (2020) Category: Mathematics courses 1 Recommended year of study:1, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Business Mathematics (2021) Category: Mathematics courses 1 Recommended year of study:1, Recommended semester: Summer