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Higher Mathematics 2

Module name (EN):
Name of module in study programme. It should be precise and clear.
Higher Mathematics 2
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Computer Science and Communication Systems, Master, ASPO 01.04.2016
Module code: KI835
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P222-0054
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V (2 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
3
Semester: 2
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam

[updated 29.06.2007]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

KI835 (P222-0054) Computer Science and Communication Systems, Master, ASPO 01.04.2016 , semester 2, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
30 class hours (= 22.5 clock hours) over a 15-week period.
The total student study time is 90 hours (equivalent to 3 ECTS credits).
There are therefore 67.5 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
KI735 Higher Mathematics 1


[updated 01.04.2003]
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Barbara Grabowski
Lecturer:
Prof. Dr. Barbara Grabowski


[updated 01.04.2003]
Lab:
Applied Mathematics, Statistics, and eLearning (5306)
Learning outcomes:
Students will be taught the stochastic methods frequently applied in technical implementations of communications systems. They will be able to apply these methods to signal transmission (optimum coding problems) and to the optimization of communications systems (performance analysis, system stability).

[updated 29.06.2007]
Module content:
1. Mathematical methods in traffic theory
1.1. Introduction to the basic principles
1.2. Markov chains
1.3. Birth and death processes
1.4. Queues
1.5. Applications in traffic measurement
  
2. Mathematical methods in information and coding theory
2.1. Entropy
2.2. Information sources, optimal source coding
2.3. Channels and optimized channel coding
2.4. Mathematical methods in pattern recognition


[updated 29.06.2007]
Recommended or required reading:
GRABOWSKI B., Stochastik für Kommunikationsinformatiker, e-learning book in the ActiveMath series
KLIMANT, Piotraschke,Schönfeld: Infomations- und Kodierungstheorie, B.G.Teubner, Leipzig, 1996
WAHRMUTH E., Mathematische Modelle in der Simulation diskreter Systeme, ZFH Koblenz, 2002

[updated 29.06.2007]
Module offered in:
SS 2017, SS 2016, SS 2015, SS 2014, SS 2013, ... 
[Sat Dec 28 10:43:33 CET 2024, CKEY=hm2, BKEY=kim, CID=KI835, LANGUAGE=en, DATE=28.12.2024]