Faculty of Information Technology, BUT

Course details

Digital Signal Processing

CZS Acad. year 2004/2005 Winter semester 6 credits

Introduction to the DSP theory. Analog signal digitalization. A/D a D/A converters. Digital signal processor architecture. DSP generations by different vendor. Floating and fixed point data representation. Instruction set. DSP programming. Development systems and tools. DSP algorithms programming (discrete convolution, correlation, digital filters IIR, FIR , LMS, DFT, FFT and IFFT). Voice and music processing using DSPs. Image processing using DSPs. DSP operations implementation using FPGAs. DSP-based embedded system design. Complex DSP system case study.

Guarantor

Language of instruction

Czech

Completion

Examination (written)

Time span

39 hrs lectures, 10 hrs pc labs, 16 hrs projects

Assessment points

40 exam, 20 half-term test, 15 exercises, 25 projects

Department

Lecturer

Subject specific learning outcomes and competences

The students are able to program basic digital signal processing algorithms on DSPs using professional development tools.

Learning objectives

To give the students the knowledge of basic digital signal processing algorithms and programming skills to be able to implement multimedia applications using DSP processors.

Study literature

  • Lecture notes
  • Internet

Fundamental literature

  • P. Lapsley, J. Bier, A. Shoham, E. A. Lee: "DSP Processor Fundamentals : Architectures and Features, IEEE Press Series on Signal Processing, IEEE, ISBN 0780334051, 1997.

Syllabus of lectures

  • Introduction to DSP theory. Analog signal digitalization. A/D and D/A converters.
  • Digital signal processor architecture. DSP generations by different vendor.
  • Floating and fixed point representation. Instruction set.
  • DSP programming. Development systems and tools.
  • DSP algorithms programming I. (discrete convolution, correlation).
  • DSP algorithms programming II. (digital filters IIR, FIR, and LMS).
  • DSP algorithms programming III. (DFT, FFT, and IFFT).
  • Voice processing using DSPs.
  • Music processing using DSPs.
  • Image processing using DSPs.
  • DSP operations implementation using FPGAs.
  • DSP-based embedded system design.
  • Complex DSP system case study.

Syllabus - others, projects and individual work of students

  • Individual sixteen-hour DSP project.

Exam prerequisites

Duty credit consists of mid-term exam passing, submitting of 5 PC lab reports and competing the project in due dates.
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