TANA09 · 4 credits · Basic level (G2F) · Matematik, Tillämpad matematik
Numerical Algorithms in Computer Science
Discontinued · replaced by TANA24
90%
passed the latest ordinary exam
TEN1 · 18 Jan 2025 · 10 students
86%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 63 students
Part of 6 programmes
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
86% passed · 63 students
- 90%10
- 100%13
- 79%19
- 81%21
Re-exams
80% passed · 5 students
- 80%5
- Pass the re-exam: 80% (5 students), compared with 86% (63 students) on the ordinary exam
- Get 4 or 5: 44% (68 students)
Show small sittings (6)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%1
- 100%1
- 33%3
- 100%3
- 33%3
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Computer assignments, compulsory attendance at sessions
- G
Main rounds
100% passed · 53 students
- 100%10
- 100%11
- 100%17
- 100%15
Later rounds
No sittings with at least 5 students.
Show small sittings (11)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
- 100%4
- 100%1
- 100%1
- 100%2
- 100%1
- 100%2
- 100%2
- 100%1
- 100%1
About the course
Aim
In computational mathematics, numerical methods are developed and analyzed for the solution of commonly occurring mathematical problems, mainly from technology and natural sciences. Important characteristics of the methods are robustness, accuracy and efficiency. As the methods are intended to be implemented on a computer, it is also important to understand how a computer processes numerical information.
After completing the course, the student should be able to:
- M1: explain basic concepts in computational science and know how a computer stores numbers and with what precision calculation operations can be performed.
- M2: use a selection of numerical methods to solve mathematical problems from calculator or computer applications.
- M3: discuss possible sources of error in numerical calculations and estimate the accuracy of calculated results.
- M4: use standard software to solve practical problems from assignments.
Content
- Error analysis and number representation: Error analysis and number representation: IEEE standard for number representation in computers. The machine precision. Analysis of calculation errors. Cancellation. Error propagation and Error sources.
- Linear algebra: Systems of linear equations. LU factorization. The condition number and error analysis. The least squares problem. The normal equations. Orthogonal bases. Projections. The QR factorization.
- Nonlinear Equations: Interval Bisection. Fixed point iteration. Convergence order. Newton-Raphson's method. Error estimation.
- Interpolation: Polynomial and Spline interpolation. B-splines. Description of curves and surfaces with Bezier polynomials.
- Examiner
- Fredrik Berntsson
- Scheduled hours
- 40 h
- Main field of study
- Matematik, Tillämpad matematik