19D041VSOS - VLSI Signal Processing

Course specification
Course title VLSI Signal Processing
Acronym 19D041VSOS
Study programme Electrical Engineering and Computing
Module Electronics and Digital Systems
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition Passed exams in the course Introduction to VLSI Systems Design or VLSI System Design and the course Digital Signal Processing from the bachelor academic studies (or their equivalents).
      The goal Learning about commonly used hardware architectures for digital signal processing and understanding their implementation aspects. Understanding technology constraints, architectural and algorithmic techniques for design and optimization of digital signal processing hardware.
      The outcome Students will be capable of designing complex VLSI systems for digital signal processing as well as for the research in this field.
      Contents of lectures Technology constraints in digital VLSI systems design. Performance, area, power and flexibility impact on a system design. Architectural techniques for signal processing hardware optimization. Hardware architectures for digital arithmetic. Algorithmic techniques for signal processing hardware optimization. Hardware architecture modeling. Data-flow graph model. Wordlength optimization.
      Contents of exercises Project
      1. K. Parhi: VLSI Digital Signal Processing Systems, John Wiley & Sons, 1999. (Original title)
      2. D. Marković, R. Brodersen: DSP Architecture Design Essentials, Springer, 2012. (Original title)
      3. F. Harris: Multirate Signal Processing for Communication Systems, Prentice Hall, 2004. (Original title)
      4. B. Parhami: Computer Arithmetic, Algorithms and Hardware Designs, Oxford University Press, 2010. (Original title)
      5. Papers from referent journals
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      Methods of teaching Lectures, mentoring and individual student's work on the project realization.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper 0
      Practical lessons 0 Oral examination 30
      Projects 50
      Colloquia 0
      Seminars 20