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Linear Algebra 2 - NMAI058
Title: Lineární algebra 2
Guaranteed by: Department of Applied Mathematics (32-KAM)
Faculty: Faculty of Mathematics and Physics
Actual: from 2019
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: taught
Language: Czech, English
Teaching methods: full-time
Guarantor: prof. Mgr. Milan Hladík, Ph.D.
doc. Mgr. Petr Kolman, Ph.D.
Teacher(s): prof. Mgr. Milan Hladík, Ph.D.
doc. Mgr. Petr Kolman, Ph.D.
Irena Penev, Ph.D.
Class: Informatika Bc.
Classification: Mathematics > Algebra
Is incompatible with: NALG086, NUMP004, NUMP003
Annotation -
Continuation of MAI057 - special matrices, determinants, eigenvalues, examples of applications of linear algebra.
Last update: FIALA/MFF.CUNI.CZ (17.02.2010)
Course completion requirements -

To get the tutorial credit, it is necessary to get at least 120 points (out of 240 possible). Points can be obtained throughout the semester from tests and homework assignments.

Those students who get at least 80 points can obtain the required points by solving additional homeworks or passing an additional test (according to the teacher's instructions).

In specific situations (long-term illness, stay abroad, etc.) the tutorial teacher may set individual conditions for obtaining the credit.

Obtaining the tutorial credit is a necessary condition for taking the exam.

Last update: Hladík Milan, prof. Mgr., Ph.D. (19.01.2024)
Literature -

W. Gareth. Linear Algebra with Applications. Jones and Bartlett Publishers, Boston, 4th edition, 2001.

C. D. Meyer. Matrix analysis and applied linear algebra. SIAM, Philadelphia, PA, 2000. http://www.matrixanalysis.com/DownloadChapters.html

G. Strang. Linear algebra and its applications. Thomson, USA, 4rd edition, 2006.

Last update: Hladík Milan, prof. Mgr., Ph.D. (22.11.2012)
Requirements to the exam -

There will an examination consisting of a written and oral part.

The written part involves several exercises. The oral part involves discussion of solutions to the set problems and additional questions on topics covered in lectures and classes.

Result of tests accomplished during the teaching period may be taken into account at the exam.

Class credits ("zapocet") are prerequisite for taking the examination

Last update: Hubička Jan, doc. Mgr., Ph.D. (13.06.2022)
Syllabus -

Inner product spaces:

  • norm induced by an inner product
  • Pythagoras theorem, Cauchy-Schwarz inequality, triangle inequality
  • orthogonal and orthonormal system of vectors, Fourier coefficients, Gram-Schmidt orthogonalization
  • orthogonal complement, orthogonal projection
  • the least squares method
  • orthogonal matrices

Determinants:

  • basic properties
  • Laplace expansion of a determinant, Cramer's rule
  • adjugate matrix
  • geometric interpretation of determinants

Eigenvalues and eigenvectors:

  • basic properties, characteristic polynomial
  • Cayley-Hamilton theorem
  • similarity and diagonalization of matrices, spectral decomposition, Jordan normal form
  • symmetric matrices and their spectral decomposition
  • (optionally) companion matrix, estimation and computation of eigenvalues: Gershgorin discs and power method

Positive semidefinite and positive definite matrices:

  • characterization and properties
  • methods: recurrence formula, Cholesky decomposition, Gaussian elimination, Sylvester's criterion
  • relation to inner products

Bilinear and quadratic forms:

  • forms and their matrices, change of a basis
  • Sylvester's law of inertia, diagonalization, polar basis

Topics on expansion (optionally):

  • eigenvalues of nonnegative matrices
  • matrix decompositions: Householder transformation, QR, SVD, Moore-Penrose pseudoinverse of a matrix

Last update: Hladík Milan, prof. Mgr., Ph.D. (28.03.2022)
 
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