Signal processing [ LELEC2900 ]
5.0 crédits ECTS
30.0 h + 30.0 h
2q
| Teacher(s) |
Macq Benoît ;
Vandendorpe Luc ;
|
| Language |
English
|
Place
of the course |
Louvain-la-Neuve
|
| Main themes |
Identical to description
|
| Aims |
At the end of this lecture, the students will be able to - make the link between the analog description of sampling and sequences, - modify the sampling rate of a discrete time signal i.e., upsample or downsample lowpass or passband signals, deterministic or random; implement these operations by means of efficient structures, in particular polyphase structures, - understand the consequences of sampling the spectrum, - design from a spectral template, finite impulse response (FIR) filters by means of different optimum and suboptimum methods, - design from a spectral template, infinite impulse response (IIR) filters; understand and use the bilinear transform; design filters based on criteria discussed in "INMA2731 : Processus stochastiques", - design systems for processing multidimentional signals, in particular images, - understand and use linear transformations for decorrelation, multiresolution analysis, and sicriminant analysis
|
| Content |
- Sampling : Shannon sampling theorem ; notions of sequence,
- Sampling rate conversion : interpolation, downsampling, lowpass and bandpass signals, deterministic and random signals,
- Structures and graph theory (introduction), polyphase components,
- Discrete Fourier transform,
- Finite impulse response filters,
- Basics of analog filters and templates,
- Bilinear transform and design of infinite impulse response filters
- Processing of random signals,
- Processing of multidimensional signals,
- Denoising and singularity detection,
- Orthogonal transforms,
- Decorrelative transforms,
- Wavelet transform,
- Linear discriminant transform,
- Non parametric (periodogram) and parametric (process identification) spectral analysis
|
| Other information |
Teaching and learning method :
There will be lectures interleaved with practical training (in teaching room or computation center with MATLAB)
Prerequisites :
INMA1731 : Random processes : estimation and prediction
Assessment :
Written examination about exercices, with notes
Could be given in English
|
Cycle et année
d'étude |
> Master [120] in Electrical Engineering
> Master [120] in Computer Science and Engineering
> Master [120] in Biomedical Engineering
> Master [120] in Electro-mechanical Engineering
> Master [120] in Mathematical Engineering
|
Faculty or entity
in charge |
> ELEC
|
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|
