PřF:Bi5440 Signals & Linear Systems - Course Information

Bi5440 Signals and linear systems

Extent and Intensity

2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).

Teacher(s)

prof. Ing. Jiří Holčík, CSc. (lecturer)
doc. Ing. Daniel Schwarz, Ph.D. (lecturer)

Guaranteed by

prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. Ing. Jiří Holčík, CSc.
Supplier department: RECETOX – Faculty of Science

Timetable

Tue 8:00–9:50 D29/347-RCX2, Wed 8:00–9:50 D29/347-RCX2

Prerequisites

Basic knowledge of differential and integral calculus, and complex numbers, resp.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Mathematical Biology (programme PřF, B-EXB)

Course objectives

At the end of the course, students should be able to: - know fundamental theoretical and methodological principles of signal and time series description and processing and linear system analysis - explain consequences and relationships between characteristics of real processes and data and applied methods and algorithms; - apply different practical approaches to data processing to obtain required analytic results; - design modified algorithms to process data of given particular characteristics

Syllabus

• 1. Systems and signals - basic vocabulary. Inspiration by practical tasks of biosignal processing and modelling biological systems. 2. Signals. Continuous signals. Basic types of continuous signals - periodical and single-shot signals. Basic manipulations with continuous signals. Decomposition of the continuous periodical signals to harmonic components - Fourier series. 3. Decomposition of continuous aperiodic signals to harmonic components - Fourier transform. Examples and applications. 4. Discrete signals. Sampling. Basic types of discrete signals and operations with them. Decomposition of discrete signals to harmonic components. Examples. 5. Discrete time Fourier transform. Discrete Fourier transform. FFT algorithm. Examples. 6. Convolution definition, practical meaning. Correlation function -autocorrelation, cross-correlation. - definitions, practical meaning. 7. Linearní transforms – Laplace transform, z-transform. Definitions, properties, applications. 8. Systems. Basic attributes of systems. Linear and nonlinear systems. Examples in biology and medicine. Description of systems - input/output description, state space description. 9. Input/output description of linear continuous systems - differential equation, system transfer function, frequency responses, pole-zero plot, impulse and transient response. 10. Input/output description of linear discrete systems - difference equation, system transfer function, frequency responses, pole-zero plot, impulse and transient response. Differences between continuous and discrete systems 11. Stability. definition. Basic relationships. Stability of linear and non-linear systems. Criteria of stability. 12. Connecting systems. Serial connection. Parallel connection. Feedback connection. Properties of the feedback connection

Literature

• Kamen, E.W. Heck B.S. Fundamentals of Signals and Systems Using the Web and Matlab. London, Prentice Hall 2000
• Oppenheim, A.V. Willsky A.S. Nawab S.H. Signals & Systems. New Jersey, Prentice Hall 1997
• Lathi, B.P. Linear Systems and Signals, Oxford, Oxford University Press 2002

Teaching methods

Lectures supported by Power Point presentations. Understanding of principles, methods and algorithms is emphasized. Students are continuously encouraged to be in an interaction with a lecturer.

Assessment methods

oral examination

Language of instruction

Czech

Further Comments

Study Materials
The course is taught annually.

• Enrolment Statistics (Autumn 2013, recent)
  
• Permalink: https://is.muni.cz/course/sci/autumn2013/Bi5440