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Course, academic year 2023/2024
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Linear algebra II (CŽV) - NMUM804
Title: Lineární algebra II (CŽV)
Guaranteed by: Department of Mathematics Education (32-KDM)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: summer
E-Credits: 5
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: cancelled
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Is provided by: NMUM104
Guarantor: doc. RNDr. Jindřich Bečvář, CSc.
RNDr. Martina Škorpilová, Ph.D.
Classification: Mathematics > Mathematics, Algebra, Differential Equations, Potential Theory, Didactics of Mathematics, Discrete Mathematics, Math. Econ. and Econometrics, External Subjects, Financial and Insurance Math., Functional Analysis, Geometry, General Subjects, , Real and Complex Analysis, Mathematics General, Mathematical Modeling in Physics, Numerical Analysis, Optimization, Probability and Statistics, Topology and Category
Incompatibility : NMUM104, NUMP004
Interchangeability : NMUM104, NUMP004
Annotation -
Last update: JUDr. Dana Macharová (10.10.2012)
Basic linear algebra course for prospective teachers.
Literature -
Last update: JUDr. Dana Macharová (10.10.2012)
  • S. Lang: Linear Algebra, Addison-Wesley Publishing Company-Reading, 1966.
  • I. Satake: Linear Algebra, Marcel Dekker, Inc., New York, 1975.
  • S. Axler: Linear Algebra Done Right, Springer, New York, 1996.

Syllabus -
Last update: JUDr. Dana Macharová (10.10.2012)
  • Systems of linear equations. Solvability, the space of solutions and its dimension, the theorem of Frobenius, Gauss elimination method; problems.
  • Determinants. Basic properties, determinat of a block matrix, the expansion of a determinant under a row and a column, the theorem on multiplication of determinants, adjugate matrix, inverse matrix, Cramer´s rule, rank of a matrix, calculation of determinants; examples.
  • Similarity, characteristic polynomial of a matrix, eigenvalues and eigenvectors, minimal polynomial of a matrix, Cayley-Hamilton theorem, similarity of matrices, simple Jordan matrix, Jordan matrix, the existence of the Jordan canonical form and the methods of evaluation, eigenvalues of symmetric matrix; examples.
  • Linear forms and dual space. Matrix and analytical expression of a linear form, dual space, dual basis; examples.
  • Bilinear forms. Matrix and analytical expression of a bilinear form, verteces, symmetrical and antisymmetrical forms, polar basis, quadratic forms, bilinear and quadratic form on real spaces, normal basis and normal expression, the law of inertia, signature, classification of forms; examples.
  • Unitary spaces. Scalar product, norm, Cauchy-Schwarz inequality, Triangle inequality, orthogonal and orthonormal basis, Gram-Schmidt orthogonalization, orthogonal transformations, orthogonal matrices; examples.

 
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