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

Teachers

Teacher: Prof. Dragoş Burileanu
Teaching Assistant: As. Drd. Şerban Mihalache

Course Description

The course presents and discusses several advanced topics in the field of digital signal processing (statistical processing of random signals, 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 practical skills related to the key theoretical concepts taught in class. The applications include various software simulations using Matlab programming environment and also dynamic systems modeling using Simulink.

Contents

Course

• 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
• Digital signal processors for real DSP applications

Laboratory

• Discrete-time deterministic signals: FFT, digital filters (Matlab review). 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: decimation, interpolation, resampling by rational factors; applications. Parametric filters
• DSP techniques for audio and speech processing applications
• DSP applications using Simulink
• Laboratory assessment

Grading

Overall laboratory activity evaluation: 25%
Homework: 25%
Course final examination (written evaluation): 50%