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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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