Graduate study programme

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Digital Signal Processing DKb1-04-18

ECTS 5 | P 30 | A 15 | L 15 | K 0 | ISVU 149720 150017 | Academic year: 2019./2020.

Course groups

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Course lecturers

BENŠIĆ TIN, Associate


Student will learn the basic methods for digital signal processing, application of FFT in signal analysis and application of Z-transform. Student will acquire practical knowledge about design of digital filters, signal processing in time and frequency domain.

Conditions for enrollment

Requirements met for enrolling in the study programme

Course description

Introduction: characteristics and classification of time discrete signals. Digital processing of continuous signals: sampling, aliasing, quantisation and reconstruction. Z-transformation, convergence areas, inverse transformation, properties. Linear time invariant (LTI) discrete systems; convolution, impulse response, transfer function. Design methods for IIR and FIR filters. Properties of discrete Fourier series and transformations. Spectral analysis with DFT and FFT. Windows. Multi-resolution signal processing, decimation and interpolation, polyphase decomposition. Basics of adaptive signal processing. Basics of multidimensional signal processing. DOS applications in speech and music processing, medical imaging, radar, communication and automation.

Student requirements

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Monitoring of students

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Obligatory literature

1. 1 V. Oppenheim, R. W. Schafer, J. R. Buck Discrete-Time Signal Processing Prentice Hall, 1999.

Pretraži literaturu na:

Recommended additional literature

1. 1 M.H. Hayes Digital Signal Processing Schaums outlines, McGraw-Hill, 1999.

2. 2 K. Mitra Digital Signal Processing: A Computer-Based Approach Mc Graw Hill, Singapore, 2006.

Course assessment

Conducting university questionnaires on teachers (student-teacher relationship, transparency of assessment criteria, motivation for teaching, teaching clarity, etc.). Conducting Faculty surveys on courses (upon passing the exam, student self-assessment of the adopted learning outcomes and student workload in relation to the number of ECTS credits allocated to activities and courses as a whole).

Overview of course assesment

Learning outcomes
Upon successful completion of the course, students will be able to:

1. design a digital FIR and IIR filter using some of the standard filter methods in MATLAB and Simulink

2. describe different analogue to digital and digital to analogue signal conversion processes

3. analyse a discrete linear time invariant (LTI) system in a time domain and transformation domain

4. interpret and compare FIR and IIR filter designs

5. define a discrete Fourier transformation (DFT) and its properties, use it in a spectral analysis and signal processing and interpret results

6. define, apply and interpret the Fast Fourier Transformation algorithms

Aktivnosti studenta: Vidi tablicu aktivnosti