Signal processing [ LELEC2900 ]
5.0 crédits ECTS
30.0 h + 30.0 h
2q
Teacher(s) |
Macq Benoît ;
Vandendorpe Luc ;
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Language |
English
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Place of the course |
Louvain-la-Neuve
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Main themes |
Identical to the contents of the course
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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
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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
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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
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Cycle et année d'étude |
> Master [120] in Mathematical Engineering
> Master [120] in Electrical Engineering
> Master [120] in Electro-mechanical Engineering
> Master [120] in Computer Science and Engineering
> Master [120] in Biomedical Engineering
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Faculty or entity in charge |
> ELEC
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