Course detail

Digital Signal Processing and Analysis

FEKT-KCZAAcad. year: 2012/2013

Properties of discrete and digital methods of signal processing, advantages and drawbacks. Linear signal filtering, digital filters of FIR and IIR types, design and realisation. Averaging methods of enhancement of signal in noise. Complex signals and their application, modulation and frequency trasnlation. Correlation and spectral analysis of deterministic and stochastic signals, identification of systems. Detection, inverse filtering and restoration of distorted signals in noise.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. Ing. Jiří Jan, CSc.

Department

Department of Biomedical Engineering (UBMI)

Learning outcomes of the course unit

Insight into digital methods of signal processing and analysis, basic application skills and experience.

Prerequisites

Knowledge of elements of signal and system theory, mathematics on Bc level

Co-requisites

Not applicable.

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.

Assesment methods and criteria linked to learning outcomes

written exam

Course curriculum

1. Classification of discrete methods of signal processing, properties and applications
2. Linear filtering - FIR filters 1
3. Linear filtering - FIR filters 2
4. Linear filtering - IIR filters 1
5. Linear filtering - IIR filters 2
6. Averaging of signals
7. Complex signals and analytic filters
8. Spectrum translation of signals
9. Correlation analysis of signals - estimation methods of the correlation function
10. Correlation analysis of signals - applications
11. Spectral analysis of deterministic signals
12. Spectral analysis of stochastic signals
13. Inverse filtering and principles of signal restoration

Work placements

Not applicable.

Aims

To provide basic theoretical knowledge and practical experience in the area of digital signal processing, analysis and restoration

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

computer lab

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

J.Jan: Digital Signal Filtering, Analysis and Restoration. IEE Publishing, London, UK, 2000 (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EECC Bc. Bachelor's

    branch BK-EST , 2 year of study, summer semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch EE-FLE , 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

Ing. Martin Vítek, Ph.D.
doc. Ing. Jiří Kozumplík, CSc.

Syllabus

Properties of discrete and digital methods of signal processing
Linear signal filtering
FIR filters
IIR filters
Averaging methods of signal enhancement in noise
Complex signals and their applications
Frequency translation of signals
Correlation analysis of signals
Spectral analysis of deterministic signals
Spectral analysis of stochastic signals
Detection of signals in noise, plain inverse filtering
Restoration of signals, Wiener filter

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

doc. Ing. Jiří Kozumplík, CSc.
Ing. Martin Vítek, Ph.D.

Syllabus

Becoming acquinted with the MATLAB
Linear signal filtering
FIR filters
IIR filters
Averaging methods of signal enhancement in noise
Complex signals and their applications
Frequency translation of signals
Correlation analysis of signals
Spectral analysis of deterministic signals
Spectral analysis of stochastic signals
Detection of signals in noise, plain inverse filtering
Restoration of signals