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13E044HSOS - Hardware and Software Signal Processing

Course specification
Course title Hardware and Software Signal Processing
Acronym 13E044HSOS
Study programme Electrical Engineering and Computing
Module Electronics and Digital Systems
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status elective
Condition
The goal Study of algorithms for digital signal processing implemented in hardware and software. Introduction to advanced topics – multirate signal processing, imperfections in real systems, digital correction. Efficient hardware and software implementations. Overview of reconfigurable DSP systems.
The outcome Students will be able to: - understand advantages of hardware and software algorithms for signal processing, - understand trade-offs and limitations of hardware and software implementations, - understand how to partition the signal processing algorithm into hardware and software, - design a DSP system on their own.
Contents
URL to the subject page http://tnt.etf.rs/~13e044hsos/
URL to lectures https://teams.microsoft.com/l/team/19%3aDgJTxvEfjAHlfSr61Y4UXKXL9wDsv4ag6ALy35aU8k81%40thread.tacv2/conversations?groupId=8979cd0d-e355-4840-8b39-ff8c22a075c4&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba
Contents of lectures Signal sampling and reconstruction. Multirate systems. Complex signal, analytical signal, Hilbert transform, quadrature signal. Complex mixer, numerically controlled oscillator, CORDIC algorithm. Pulse shaping filters. Digital correction, required resources. Systems for hardware-software signal processing. RFSoC. Current state of the art in hardware-software signal processing.
Contents of exercises Computer simulations in SciPy, Octave, Matlab. Simulation of hardware implementations in VHDL/Verilog simulators. Work with systems for signal processing.
Literature
  1. F. Harris, “Multirate Signal Processing for Communication Systems”, Prentice Hall, 2004 (Original title)
  2. J. Proakis, D. Manolakis, “Digital Signal Processing”, Pearson, 2006 (Original title)
  3. Papers from peer-reviewed journals
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
3 1 1
Methods of teaching Lectures. Practices, presentations, interactive design sessions. Review of state of the art. Computer simulations. Individual work on projects.
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures Test paper
Practical lessons 20 Oral examination 30
Projects
Colloquia
Seminars 50