Subject Datasheet
Download PDFBudapest University of Technology and Economics | |
Faculty of Transportation Engineering and Vehicle Engineering |
1. Subject name | Analitical Methots in System Technique I. | ||||
2. Subject name in Hungarian | Analitikus módszerek a rendszertechnikában I. | ||||
3. Code | BMEKOVJD001 | 4. Evaluation type | exam grade | 5. Credits | 4 |
6. Weekly contact hours | 2 (0) Lecture | 0 (0) Practice | 0 (0) Lab | ||
7. Curriculum | PhD Programme |
8. Role | Basic course |
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9. Working hours for fulfilling the requirements of the subject | 120 | ||||
Contact hours | 28 | Preparation for seminars | 30 | Homework | 15 |
Reading written materials | 15 | Midterm preparation | 0 | Exam preparation | 32 |
10. Department | Department of Aeronautics and Naval Architectures | ||||
11. Responsible lecturer | Dr. Zobory István | ||||
12. Lecturers | Dr. Zobory István | ||||
13. Prerequisites | |||||
14. Description of lectures | |||||
Sets. Basic number sets. Numerical sequences and numerical series. Convergency. Defining functions. Description of functions. Multivariate functions. Limit value, continuity and differentiability. Concept of Riemann-integral. Convergency concepts. Important function series: Taylor-series and Fourier-series. Basic numerical methods. Polynomial interpolations. Lagrange-interpolation, Hermite-interpolation and spline-interpolation. The method of least square. Numerical solution to algebraic equations. Method of intervallum-dividing. String-method. Section method. Tangent method. Successive approximation. Numerical integration. The Newton-Cotes procedure. The trapeze-rule. The Simpson-trule. Linear algebra and matrix calculus. Linear space. Linear sub-space. Linear independence. Generator-system. Basis. Scalar product. Ortogonality. Norma.Metric space. Matrices and vectors. Standard basis. Description of the elements of the linear space by using different bases. Homogeneous linear mappings and their matrices. Rang of matrices. Basis-dependence of the matrix of a linear mapping. Matrix product. Determinants. Inverse matrix. Linear set of equations. Condition of solvability based on the rang of the coefficient matrix. The Gaussean algorithm. Improvement of the accuracy. Iterative methods. The accelerating algorithm of Seidel. Treatment of contradictory (principally not solvable) set of equations. | |||||
15. Description of practices | |||||
16. Description of labortory practices | |||||
17. Learning outcomes | |||||
A. Knowledge
B. Skills
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18. Requirements, way to determine a grade (obtain a signature) | |||||
Accepted homework sent before the deadline and written exam. | |||||
19. Opportunity for repeat/retake and delayed completion | |||||
According to the TVSZ. | |||||
20. Learning materials | |||||
1. Zobory, I.: Analitikus módszerek a rendszertechnikban I. Egyetemi jegyzet. BME Vasúti Járművek és Járműrendszeranalízis Tanszék. Budapest, 2011. 2. Rudin, W.: A matematikai analízis alapjai. Tipotex Kft., Budapest, 2010. |
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Effective date | 27 November 2019 | This Subject Datasheet is valid for | Inactive courses |