Advanced Techniques in Digital Signal Processing

Course in Bachelor programme (4th year, series E)


Teacher: Prof. Dragoş Burileanu
Teaching Assistant: Lect. Andi Buzo

Course Description

The course presents and discusses several advanced topics in the field of digital signal processing (random signal processing, spectral analysis, linear and nonlinear adaptive filtering, multirate signal processing), with applications in communication and audio and speech processing. The aim is to understand the phenomena underlying the studied techniques and also their implementation in real systems, as well as to introduce modern signal processor architectures and their use in real-time processing systems.
The laboratory’s aim is acquiring key practice concepts taught in class. The applications include mainly software simulations using a high-level programming environment.



  • Statistical signal processing
  • Spectral analysis and parametric estimation for random discrete signals
  • Adaptive filters. Linear prediction applied in speech signal coding; adaptive filtering techniques used in the acoustic echo cancelation in distance talking communication systems
  • Multirate signal processing
  • Artificial neural networks. Applications in signal processing
  • Digital processing techniques and signal processors for audio applications


  • Discrete-time random signals: representation, statistical parameters
  • Spectral analysis for random signals. Linear estimation; the Wiener filter
  • Adaptive filters. The LMS and nLMS algorithms; applications
  • Multirate signal processing
  • DSP techniques for audio and speech processing applications
  • Laboratory assessment


Overall laboratory activity evaluation: 20%
Homework: 20%
Course final examination (written evaluation): 60%