Course code 
02 36 6254 00 
Number of ECTS points 
5 
Course title in the language of instruction 
Signal Processing 
Course title in Polish 
Signal Processing (Przetwarzanie sygnałów) 
Course title in English 
Signal Processing 
Language of instruction 
English 
Form of classes 

Lecture 
Tutorials 
Laboratory 
Project 
Seminar 
Other 
Total of teaching hours during semester 
Contact hours 
30 

30 


0 
60 
Elearning 
No 
No 
No 
No 
No 
No 

Assessment criteria (weightage) 
0.40 

0.60 


0.00 


Unit running the course 
Instytut Elektroniki 
Course coordinator 
prof. dr hab. inż. Paweł Strumiłło 
Course instructors 

Prerequisites 
The student knows fundamentals of mathematical analysis and matrix algebra 
Course learning outcomes 
 Distinguish between types of biological signals
 Select digitazation parameters for analog signals
 Calculate and interpret the Fourier spectrum of the signal
 Use appropriate digital filters in biomedical applications
 Detect components of biomedical signals in the time and frequency domain
 Use basic methods of statistical classification of medical data

Programme learning outcomes 
 null
 null
 null

Programme content 
LECTURE:
1. Biological signals  classification
2. Measurement of biological signals, sources of interference
3. Linear systems and weave
4. Spectral analysis of signals, properties and applications
5. Sampling and quantization of signals  digital signals
6. Digital filtering of signals
7. Models of random signals, correlation analysis
8. Analogtodigital and digitaltoanalog processing
9. Sample systems and programs for biological signal analysis
LABORATORY:
Part I: Introduction to signal processing in Python (8 laboratory exercises)
1. Data display, board activities and functions
2. Saving and loading files: text, binary, Matlab and wave files
3. Signal display
4. Fourier transformation of signals
5. Digital filtering of signals
Part II: Project on processing and analysis of biological signals 
Assessment methods 
The written test will verify the following skills:
1. Recognizing different types of biomedical signals
2. Selecting proper recording parameters for digital acquisition of analog signals
3. Computing and interpreting the Discrete Fourier Transform of signals
The laboratory and project will verify the skills:
4. Applying appropriate digital filters to achieve the given processing objective
5. Detecting specific components of biomedical signals in time and spectrum domain
6. Applying basic statistical methods for medical data classification

Grading policies 
A written form verifying knowledge of lecture material and a written project report from and project presentation. 
Course content 
LECTURE:
1. Biomedical signals ? characterization and classification
2. Measurements of biological signals, sources of noise
3. Linear systems and convolution
4. Spectral analysis of signals, properties and applications
5. Sampling and quantization of signals Digital signals
6. Digital filtering of signals
7. Random models of signals models, correlation analysis
8. Analogtodigital and digitaltoanalog conversion
9. Case studies: systems and programs for analysis of biomedical signals
LABORATORATORY:
Part I: Introduction to Signac processing in Python (8 laboratory sessions)
1. Data visualization, array operations and functions
2. Storing/loading: text, binary, Matlab and wave files
3. Plotting signals
4. Fourier transform of signals
5. Digital filtering of signals
Part II: Work on a project related to selected problems of signal processing and analysis 
Basic reference materials 
 Notatki wykładowe przekazane przez prowadzącego

Other reference materials 
 Tomasz Zieliński , Cyfrowe przetwarzanie sygnałów. Od teorii do zastosowań, WKiŁ, 2009, ISBN: 9788320616408
 The Scientist and Engineer's Guide to Digital Signal Processing by Steven W. Smith (www.dspguide.com)

Average student workload outside classroom 
66 
Comments 

Updated on 
20190831 09:25:36 
Archival course yes/no 
no 