Applied signal processing
Signal processing involves techniques to recover important information from signals and to suppress irrelevant parts of those signals. The aim of this course is to provide the students with knowledge of standard techniques and applications in digital signal processing. These are relevant for the design and implementation of communication systems, control systems and other measurement systems such as biomedical instrumentation systems. The students are also given the opportunity to practically apply some of the techniques to semi-real signal processing problems and will be given insight into current practice in industry.
•in both time-domain and frequency-domain analyse the effect of sampling, linear filtering and signal reconstruction
•explain the relation between the Fourier transform, discrete Fourier transform and fast Fourier transform and apply the discrete Fourier transform to perform block based linear filtering
•apply linear filter design techniques to construct FIR and IIR filters satisfying given specifications
•apply LMS, RLS and Kalman filters to linear adaptive filtering problems and do simplified analysis regarding stability and rate of convergence
•apply multirate techniques to signal processing problems to increase efficiency
•explain how quantization and finite word lengths affect the signal and algorithm quality and calculate the effect on the SNR
•discuss the effect of using a linear finite dimensional model as an approximation for an infinite dimensional linear systems.
•implement signal processing algorithms on a DSP-system