Module also offered within study programmes:
General information:
Name:
Applications of Digital Signal Processors
Course of study:
2017/2018
Code:
IES-1-705-s
Faculty of:
Computer Science, Electronics and Telecommunications
Study level:
First-cycle studies
Specialty:
-
Field of study:
Electronics and Telecommunications
Semester:
7
Profile of education:
Academic (A)
Lecture language:
English
Form and type of study:
Full-time studies
Course homepage:
 
Responsible teacher:
dr inż. Rumian Roman (rumian@agh.edu.pl)
Academic teachers:
dr inż. Rumian Roman (rumian@agh.edu.pl)
Module summary

Introduction to digital spectral analysis and digital filtering with practical applications.

Description of learning outcomes for module
MLO code Student after module completion has the knowledge/ knows how to/is able to Connections with FLO Method of learning outcomes verification (form of completion)
Social competence
M_K001 Student understand necessity of giving the society actual and clear information and opinions upon digital signal processing methods ES1A_K06 Participation in a discussion
Skills
M_U001 Students can use tools and algorithms of digital signal processing ES1A_U08, ES1A_W13 Execution of laboratory classes,
Test,
Examination
M_U002 Students can analyze signals and systems in time domain and frequency domain ES1A_U08, ES1A_W18, ES1A_W13 Execution of laboratory classes,
Test,
Examination
M_U003 Student can design basic digital signal processing systems ES1A_W20, ES1A_W13 Execution of laboratory classes,
Test,
Examination
M_U004 Student can interpret information from literature about signal processing algorithms ES1A_K01, ES1A_U01, ES1A_U06 Execution of laboratory classes,
Test,
Examination
Knowledge
M_W001 Student knows definitions, concepts and algorithms of digital signal processing ES1A_U08, ES1A_W18, ES1A_W20, ES1A_W13 Execution of laboratory classes,
Test,
Examination
FLO matrix in relation to forms of classes
MLO code Student after module completion has the knowledge/ knows how to/is able to Form of classes
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Zaj. terenowe
Zaj. warsztatowe
Others
E-learning
Social competence
M_K001 Student understand necessity of giving the society actual and clear information and opinions upon digital signal processing methods + - - - - - - - - - -
Skills
M_U001 Students can use tools and algorithms of digital signal processing + - + - - - - - - - -
M_U002 Students can analyze signals and systems in time domain and frequency domain + - + - - - - - - - -
M_U003 Student can design basic digital signal processing systems + - + - - - - - - - -
M_U004 Student can interpret information from literature about signal processing algorithms + - - - - - - - - - -
Knowledge
M_W001 Student knows definitions, concepts and algorithms of digital signal processing + - + - - - - - - - -
Module content
Lectures:
-
Laboratory classes:
  1. Introduction to CrossCore Embedded Studio and ADSP-21489 EZ-Board
  2. Fixed-point arith­metic (fixed-point) and float­ing point CPU of the ADSP-21489
  3. Imple­men­ta­tion of Delay and echo
  4. The SISD and SIMD imple­men­ta­tion of sam­ple based ver­sion FIR fil­ters
  5. The SISD and SIMD imple­men­ta­tion of sam­ple based ver­sion IIR fil­ters
Student workload (ECTS credits balance)
Student activity form Student workload
Summary student workload 75 h
Module ECTS credits 3 ECTS
Participation in lectures 14 h
Participation in laboratory classes 24 h
Preparation of a report, presentation, written work, etc. 25 h
Realization of independently performed tasks 12 h
Additional information
Method of calculating the final grade:

1. Positive final evaluation from, both, laboratory exercises and examination is required.
2. Mean value is calculated from marks obtained by a student during all final laboratory evaluations and all examination dates.
3. Final mark is calculated using the following formulae:
if mean>4.75 then OK:=5.0 else
if mean>4.25 then OK:=4.5 else
if mean>3.75 then OK:=4.0 else
if mean>3.25 then OK:=3.5 else OK:=3
4. If positive results from laboratory and examination are obtained during the first attempt (date) and the final mark is lower than 5.0, then the final mark is increased by 0.5.

Prerequisites and additional requirements:

Elementary/basic knowledge of: mathematics, numerical methods, theory of signals and systems, programming in Matlab.

Recommended literature and teaching resources:

1. A.V. Oppenheim, R.W. Schafer: Discrete-Time Signal Processing, Prentice-Hall, 1989.
2. R. G. Lyons: Understanding Digital Signal Processing. Addison Wesley Longman, 1997, 2004.
3. E.C. Ifeachor, B.W. Jervis: Digital Signal Processing: A Practical Approach. Addison-Wesley 1993.
4. D.K. Manolakis, V.K. Ingle: Applied Digital Signal Processing. Cambridge University Press 2011.
5. S.D. Stearns, R.A. David: Signal Processing Algorithms in Matlab. Prentice Hall 1996.
6. S. W. Smith: The Scientist and Engineer's Guide to Digital Signal Processing, California Technical Publishing 1997.
7. J.G. Proakis, D.K. Manolakis: Digital Signal Processing: Principles, Algorithms, Applications. Prentice-Hall 2006.

Scientific publications of module course instructors related to the topic of the module:

Additional scientific publications not specified

Additional information:

Participation in EU POWER English language improvement course in 2018.