Course detail

Statistics in Telecommunication

FEKT-NSTKAcad. year: 2015/2016

The proposed structure of the subject focuses on the use of selected mathematical techniques in modern communication signal processing and wireless communication theory. The goal is to present students with master's degree program Electronics and Communication Engineering specialized mathematical apparatus, which is essential to understanding the principles of modern wireless communications.

Learning outcomes of the course unit

Students after completing the course should be able to solve problems associated with verification and testing assumptions and properties of the investigated phenomena and data files in the telecommunications field.
The student is able to:
- Quantifying the probability of the event
- Distinguishing between the random variables and describe their characteristics
- To test the hypothesis by parametric and non-parametric way
- Describe the probability density by Gaussian mixture models
- Estimating the shape of the spectrum and identify the spectral components
- Identify and test the presence of a signal in noise

Prerequisites

A student who register the course should be able to: - To compose a simple program in Matlab - Practicing a mathematical calculation procedures

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

ANDĚL, J., Statistická analýza časových řad. SNTL, Praha (CS)
LEVIN, B.: Teorie náhodných procesů a její aplikace v radiotechnice, SNTL Praha (CS)
GOPI, E., S.: Algorithm Collections for Digital Signal Processing Applications Using Matlab, Springer, 2007, 190 pp., ISBN 978-1-4020-6409-8 (EN)
KAY, S.: Intuitive Probability and Random Processing using MATLAB, Springer 2005, 833 pp., ISBN 0-387-24157-4 (EN)
STEHLÍKOVÁ, B. a kol.: Metodologie výzkumu a statistická inference. 9. vyd. Brno: Folia univ. agric. et silvic. Mendel. Brun., 2009. II. ISBN 978-80-7375-362-7. (CS)
KOBAYASHI, H. et al: Probability, random processes, and statistical analysis, Cambridge University Press, 2012, 780 pp., ISBN 978-0-521-89544-6 (EN)

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations. Techning methods include lectures, computer laboratories.

Assesment methods and criteria linked to learning outcomes

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every. Tests written during semester (2x20 points), final exam (60 points).

Language of instruction

English

Work placements

Not applicable.

Course curriculum

1. Introduction to the subject, probability theory, dependent and independent experiments, conditional probability.
2. The definition and the type of random variables, the characteristics of random variables, an entropy.
3. Multinomial random variables.
4. Functions of continuous random variables.
5. The central limit theorem and the law of large numbers.
6. Introduction to the theory of statistics, point and interval estimation, confidence intervals
7. Hypothesis testing, the parametric and the nonparametric approach.
8. Gaussian mixed models.
9. Random processes (stationarity, ergodicity of stationary processes, energy spectrum, Gaussian process).
10. Transformation of random processes.
11. Orthogonal transformation, Karhunen-Loev transformation, PCA.
12. Spectrum estimation techniques (parametric and nonparametric methods).
13. Detection of hidden signals in noises

Aims

The proposed structure of the subject focuses on the use of selected mathematical techniques in modern communication signal processing and wireless communication theory. The goal is to present students with master's degree program Electronics and Communication Engineering specialized mathematical apparatus, which is essential to understanding the principles of modern wireless communications.

Specification of controlled education, way of implementation and compensation for absences

Evaluation of activities is specified by a regulation, which is issued by the lecturer responsible for the course annually.

Classification of course in study plans

  • Programme EEKR-MN Master's

    branch MN-EST , 1. year of study, summer semester, 5 credits, optional specialized

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Computer exercise

26 hours, compulsory

Teacher / Lecturer