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LTH Courses

Faculty of Engineering | Lund University

Courses given 2016/17 by Centre of Mathematical Sciences

◄ 16/17 ►

Mathematical Statistics

Course Code Link to complete information about the course; study periods, programmes etc. Credits Cycle G1: Basic level
G2: Upper basic level
A: Advanced level 		Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. S.Ex. stud. The course is suitable for incoming exchange students. Language Language of the course:
E: The course is given in English
E1: The course is given in English upon request
E2: The course may be given in English
S: The course is given in Swedish 		Course Name Foot­note Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule 		  16/17
sp1		 16/17
sp2		 16/17
sp3		 16/17
sp4
F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions)
FMSF15 7.5 G2 BME, C, D, E, F, I, Pi X E1 Markov Processes KS KE U W T 26 16 6 0 140
FMS086 7.5 G2 B, BME, K, N - S Mathematical Statistics KS KE U W T 26 16 8 1 140
FMS140 7.5 G2 W - S Mathematical Statistics, Basic Course KS KE U W T 16 16 20 2 130
FMSF10 7.5 G2 BME, C, D, E, F, I, M, MWIR, Pi X E1 Stationary Stochastic Processes X Please see footnote below. KS KE U W T 26 16 6 0 140
FMS065 7.5 G2 BME, C, Pi, RH - E1 Statistical Methods for Safety Analysis KS KE U W T 28 14 12 0 120
FMSN25 7.5 A F, I, Pi X E1 Valuation of Derivative Assets KS KE U W T 32 26 6 1 120
FMS012 9 G2 C, D, I, Pi - S Mathematical Statistics, Basic Course KS KE U W T 18 14 4 0 85 18 14 4 0 85
FMS012 F 18 14 4 0 85 18 14 4 0 85
FMS161 7.5 A F, I, Pi X E1 Financial Statistics KS KE U W T 28 14 16 5 120
FMS032 7.5 G2 L, V - S Mathematical Statistics, Basic Course KS KE U W T 26 16 8 0 140
FMSF20 7.5 G2 E - S Mathematical Statistics, Basic Course KS KE U W T 26 16 8 0 140
FMS051 7.5 A BME, C, D, E, F, I, Pi X E1 Mathematical Statistics, Time Series Analysis KS KE U W T 26 12 12 5 120
FMSN20 7.5 A BME, C, D, E, F, Pi X E1 Spatial Statistics with Image Analysis KS KE U W T 28 0 21 4 120
FMSN15 7.5 A F, I, Pi, RH X E1 Statistical Modelling of Multivariate Extreme Values KS KE U W T 28 14 9 1 120
FMS091 7.5 A BME, D, F, I, Pi X E1 Monte Carlo and Empirical Methods for Stochastic Inference KS KE U W T 26 0 14 5 120
FMSF05 7.5 G2 BME, F, I, Pi X E1 Probability Theory KS KE U W T 22 14 0 0 160
FMSN35 7.5 A BME, C, D, E, F, I, Pi X E Stationary and Non-stationary Spectral Analysis X Please see footnote below. KS KE U W T Course on hold Course on hold: The course is not given this academic year, but is planned to be given next academic year.
FMS072 7.5 G2 BME, D, E, F, MLIV, MWIR, N, Pi, W X E1 Design of Experiments KS KE U W T 14 14 14 1 150
FMSN05 3 A Pi X E International Project Course-Mathematical Modelling X Please see footnote below. KS KE U W T 0 0 0 10 40
FMSN30 7.5 A BME, D, F, I, L, M, Pi X E1 Linear and Logistic Regression X Please see footnote below. KS KE U W T 24 0 26 2 120
FMSN40 9 A I X E1 Linear and Logistic Regression with Data Gathering X Please see footnote below. KS KE U W T 26 0 30 5 120
FMS035 7.5 G2 C, M - S Mathematical Statistics, Basic Course KS KE U W T 26 16 8 0 140
FMS155 7.5 A D, F, I, Pi X E1 Statistical Modelling of Extreme Values KS KE U W T 28 14 9 1 120

FMSF10 (C, D, E, I) Stationary Stochastic Processes: Only one of the courses FMS045 and FMSF10 may be included in a degree.
FMSN35 (BME, C, D, E, F, I, Pi) Stationary and Non-stationary Spectral Analysis: The course is offered every other academic year and will next be offered in 2017/18.
FMSN05 (Pi) International Project Course-Mathematical Modelling: Limited number of participants. Specific application procedure. The course is given in August.
FMSN30 (I) Linear and Logistic Regression: Only one of the courses FMSN30 and FMSN40 may be included in a degree.
FMSN40 (I) Linear and Logistic Regression with Data Gathering: Compulsory course in the elective block ‘Mathematical Modelling’ for students admitted autumn 2014. The course is also an optional programme course. Only one of the courses FMSN30 and FMSN40 may be included in a degree.

Mathematics

Course Code Link to complete information about the course; study periods, programmes etc. Credits Cycle G1: Basic level
G2: Upper basic level
A: Advanced level 		Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. S.Ex. stud. The course is suitable for incoming exchange students. Language Language of the course:
E: The course is given in English
E1: The course is given in English upon request
E2: The course may be given in English
S: The course is given in Swedish 		Course Name Foot­note Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule 		  16/17
sp1		 16/17
sp2		 16/17
sp3		 16/17
sp4
F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions)
FMA430 6 G1 B, BI, BME, C, D, IDA, IEA, K, L, N, V - S Calculus in Several Variables KS KE U W T 42 16 2 0 102
FMA430 F, I, IBYA, IBYV, W 42 16 2 0 102
FMA430 E, M, MD 42 16 2 0 102
FMAN20 7.5 A BME, C, D, E, F, L, Pi X E1 Image Analysis KS KE U W T 32 0 0 2 166
FMAF30 5 G2 IBYA, IBYI, IBYV - S Mathematical Statistics KS KE U W T 30 32 0 0 71
FMAF20 4 G2 IEA - S Probability Theory KS KE U W T 24 24 0 0 54
FMA661 7.5 G2 IDA - S Probability Theory and Discrete Mathematics KS KE U W T 36 38 0 0 126
FMAA05 15 G1 B, BI, C, D, E, F, I, K, L, N, Pi, V, W - S Calculus in One Variable KS KE U W T 50 24 0 0 128 50 24 0 0 128
FMA260 7.5 A F, Pi X E1 Functional Analysis and Harmonic Analysis KS KE U W T 20 10 0 0 108 8 4 0 0 50
FMA120 6 A BME, C, D, E, F, Pi X E1 Matrix Theory KS KE U W T 16 8 0 1 56 14 6 0 1 58
FMAN15 7.5 A D, F, Pi X E Nonlinear Dynamical Systems KS KE U W T 16 6 0 0 78 14 8 0 0 78
FMA645 13.5 G1 IBYA, IBYI, IBYV, IDA, IEA - S Calculus KS KE U W T 14 26 0 0 40 44 26 0 0 92 28 26 0 0 66
FMAA01 15 G1 BME, M, MD - S Calculus in One Variable KS KE U W T 30 16 0 0 88 36 16 0 0 81 36 16 0 0 81
FMA085 4.5 G1 Pi - S Mathematical Communication KS KE U W T 10 8 0 1 12 6 2 0 1 8 2 0 0 0 0 6 6 0 4 60
FMA420 6 G1 F, Pi, W - S Linear Algebra KS KE U W T 38 16 0 0 106
FMA420 I, M, MD 38 16 0 0 106
FMA420 BI, C, E, L, N, V X Please see footnote below. 38 16 0 0 106
FMA420 BME, D 38 16 0 0 106
FMAF01 7 G2 BME, F, N, Pi - E1 Mathematics - Analytic Functions KS KE U W T 40 16 0 1 127
FMAF01 BME, C, D, E, I X Please see footnote below. 40 16 0 1 127
FMAN45 7.5 A BME, D, E, F, Pi X E Machine Learning KS KE U W T 32 0 0 2 166
FMAA10 3 G1 Pi - S Mathematical Modelling X Please see footnote below. KS KE U W T 6 0 0 2 72
FMAN30 7.5 A BME, C, D, E, F, Pi X E1 Medical Image Analysis KS KE U W T 32 0 0 3 165
FMA051 6 A BME, D, E, F, I, Pi X E1 Optimization X Please see footnote below. KS KE U W T 32 14 4 1 109
FMA250 7.5 A F, Pi X E1 Partial Differential Equations with Distribution Theory X Please see footnote below. KS KE U W T 28 14 0 0 158
FMAN40 3 A BME, C, D, E, F, Pi X E1 Project in Applied Mathematics KS KE U W T 0 0 0 10 70
FMAN40 BME, C, D, E, F, Pi 0 0 0 10 70
FMAA25 7.5 G1 C, D, E, F, Pi X E1 Discrete Mathematics KS KE U W T 32 16 0 0 152
FMAA25 C, D, E, F, Pi 32 16 0 0 152
FMAF05 7 G2 BME, F, N, Pi - E1 Mathematics - Systems and Transforms KS KE U W T 40 16 0 1 127
FMAF05 BME, C, D, E, I X Please see footnote below. 40 16 0 1 127
FMAN35 3 A D, E, F, Pi X E1 Project in Mathematics KS KE U W T 0 0 0 10 70
FMAN35 D, E, F, Pi 0 0 0 10 70
FMAN10 7.5 A C, D, F, Pi X E1 Algebraic Structures X Please see footnote below. KS KE U W T 28 10 0 0 162
FMAF10 5 G2 B, BME, C, D, K, L, M, W - S Applied Mathematics - Linear systems X Please see footnote below. KS KE U W T 26 10 4 0 93
FMA270 6 A BME, C, D, E, F, Pi X E1 Computer Vision KS KE U W T 26 0 0 2 132
FMAA20 7.5 G1 B, K, W - S Linear Algebra with Introduction to Computer Tools KS KE U W T 46 24 0 0 130
FMA240 6 G2 BME, D, E, F, Pi X E1 Linear and Combinatorial Optimization KS KE U W T 26 0 4 1 130
FMA111 6 A D, F, Pi - S Mathematical Structures KS KE U W T 28 14 0 0 118
FMA021 7.5 A D, E, F, M, Pi - S Applied Mathematics KS KE U W T 24 12 2 0 62 22 14 2 0 62
FMAN01 7.5 A E, F, Pi, W X E1 Biomathematics X Please see footnote below. KS KE U W T Course on hold Course on hold: The course is not given this academic year, but is planned to be given next academic year.
FMA435 7.5 G1 Pi - S Calculus in Several Variables KS KE U W T 42 16 2 0 108 8 6 0 0 26
FMAN25 7.5 A D, E, F, Pi X E1 Calculus of Variations KS KE U W T 18 0 0 0 82 16 0 0 0 84
FMAF25 3 G2 Pi - S Mathematical Modelling with Statistical Applications, Project KS KE U W T 16 0 0 3 61
FMA656 4.5 G1 IBYA, IBYI, IBYV, IDA, IEA - S Mathematics, Linear Algebra KS KE U W T 28 26 0 0 66

FMA420 (V) Linear Algebra: The course is an admission requirement for FMN140
FMAF01 (D) Mathematics - Analytic Functions: Can together with FMAF05 replace FMAF10. Can also be taken as an elective course in the 4th or 5th year.
FMAA10 (Pi) Mathematical Modelling: All the projects must be approved during the current academic year. Thus one may not save results on single projects till a later year.
FMA051 (BME, D, E, F, Pi) Optimization: Written examination before Christmas so that exchange students may participate.
FMA051 (I) Optimization: Compulsory course in the elective block ‘Mathematical Modelling’ for students admitted autumn 2014. The course is also an optional programme course. Written examination before Christmas so that exchange students may participate.
FMA250 (F, Pi) Partial Differential Equations with Distribution Theory: The course is offered every other academic year and will be given in 2016/17, 2018/19.
FMAF05 (C) Mathematics - Systems and Transforms: Only one of the courses FMAF05 and FMAF10 may be included in a degree.
FMAF05 (D) Mathematics - Systems and Transforms: Can together with FMAF01 replace FMAF10. Only one of the courses FMAF05 and FMAF10 may be included in a degree.
FMAN10 (C, D, F, Pi) Algebraic Structures: The date and time of the exam is announced by the course lecturer. The course is to be studied together with MATM11, which is given by the division for Mathematics of the Faculty of Science.
FMAF10 (C) Applied Mathematics - Linear systems: Only one of the courses FMAF05 and FMAF10 may be included in a degree.
FMAF10 (D) Applied Mathematics - Linear systems: Can be replaced by FMAF01 and FMAF05 together. Only one of the courses FMAF10 and FMAF05 may be included in a degree.
FMAN01 (E, F, Pi, W) Biomathematics: The course is offered every other academic year and will next be offered in 2017/18.

Numerical Analysis

Course Code Link to complete information about the course; study periods, programmes etc. Credits Cycle G1: Basic level
G2: Upper basic level
A: Advanced level 		Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. S.Ex. stud. The course is suitable for incoming exchange students. Language Language of the course:
E: The course is given in English
E1: The course is given in English upon request
E2: The course may be given in English
S: The course is given in Swedish 		Course Name Foot­note Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule 		  16/17
sp1		 16/17
sp2		 16/17
sp3		 16/17
sp4
F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions)
FMNN25 7.5 A D, E, F, Pi X E1 Advanced Course in Numerical Algorithms with Python/SciPy KS KE U W T 28 0 0 3 169
FMNN01 7.5 A BME, F, Pi X E Numerical Linear Algebra KS KE U W T 36 0 0 6 160
FMN100 6 A C, D, E, F, Pi X E1 Numerical Methods in CAGD X Please see footnote below. KS KE U W T 28 0 0 4 130
FMNN10 8 A BME, F, I, Pi X E1 Numerical Methods for Differential Equations KS KE U W T 48 0 0 3 160
FMNN05 7.5 A D, F, Pi X E1 Simulation Tools KS KE U W T 28 0 0 3 169
FMN140 6 G2 V - S Scientific Computing KS KE U W T 24 0 26 1 52 2 0 10 1 41
FMNN30 7.5 A F, Pi X E Iterative Solution of Large Scale Systems in Scientific Computing X Please see footnote below. KS KE U W T Course on hold Course on hold: The course is not given this academic year, but is planned to be given next academic year.
FMN011 6 G2 C, D X E1 Numerical Analysis KS KE U W T 48 12 0 3 100
FMN050 6 G2 BME, E, I X E1 Numerical Analysis X Please see footnote below. KS KE U W T 48 10 0 3 100

FMN100 (C, D, E, F, Pi) Numerical Methods in CAGD: Please note that the contents of the course are partly (3 credits) the same as in FMA135.
FMNN30 (F, Pi) Iterative Solution of Large Scale Systems in Scientific Computing: The course is offered every other academic year and will next be offered in 2017/18.
FMN050 (I) Numerical Analysis: Compulsory course in the elective block ‘Mathematical Modelling’ for students admitted autumn 2014. The course is also an optional programme course.

Bachelor's Projects of the Department

The list contains the bachelor's projects which are given by the department and which programme each bachelor's project is included in.

Course Code Credits Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. Course Name Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
FMSL01 15 C, D, E, F, I, Pi Bachelor Project in Mathematical Statistics KS KE U W
FMAL01 15 C, D, E, F, Pi Bachelor Project in Mathematics KS KE U
FMNL01 15 D, E, F Bachelor Project in Numerical Analysis KS KE U

Degree Projects of the Department

The list contains the degree projects which are given by the department and which programme each degree project is included in.

Course Code Credits Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. Course Name Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
FMS820 30 BME, C, D, E, F, I, Pi, RH Degree Project in Mathematical Statistics for Engineers KS KE U W
FMA820 30 BME, C, D, E, F, I, M, Pi Degree Project in Mathematics for Engineers KS KE U W
FMN820 30 D, E, F, I, Pi Degree Project in Numerical Analysis KS KE U W