EE2S31 Signal processing
In this course the following topics are discussed:
Digital signal processingThe part on signal processing considers in particular one-dimensional signals and discusses digital filter design, filter structures, the DFT spectral analysis, filter implementation, and multirate filters.
- Repetition ((discrete-time) signal processing, poles and zeros, filter functions)
- Discrete Fourier transform (frequency domain sampling, properties, convolution using DFT (FFT))
- Spectral analysis
- Sampling and reconstruction
- Time Discrete filter structures
- Digital Filter Design
- Multirate filters
- Quantization and rounding errors
Stochastic processes:The part on stochastic processes introduces the concept of stochastic models and random processes to describe systems and signals that are not deterministic in nature.
- Pairs of random variables
- Random vectors & conditional probability models
- Sums of random variables,
- Derived random variables
- moment generating function
- central limit theorem.
- Deviation of RVs from its expected value:Markov ineq., Chebyshev ineq. and the Chernoff bound.
- Sample mean, unbiased estimators, consistency.
- Estimation of Random variables, blind estimation, conditional estimation, MMSE, MAP and ML estimators.
- Stochastic processes.
- Estimation of autocorrelation functions, ergodicity, the autocorrelation function & signal processing for WSS signals.
- The autocorrelation function & signal processing, PSD, CPSD & frequency domain relationships.
dr.ir. Richard Heusdens
Audio and acoustic signal processing, distributed signal processing, information theory (source coding), speech enhancement
dr.ir. Richard Hendriks
Audio signal processing, signal processing for hearing aids, biomedical signal processing
Last modified: 2017-09-28