Courses
You will find below slides related to the following courses :
- Estimation theory : notions of bias and variance, Cramér-Rao bounds, minimum variance unbiased estimation, maximum likelihood estimation, least-squares estimation, method of moments. Introduction to Bayesian estimation.
- Array processing : signals received on an array of sensors, spatial filtering, adaptive beamforming, robust adaptive beamforming, partially adaptative and reduced-rank beamforming (supplementary document : A short overview of adaptive multichannel filters SNR loss analysis), direction of arrival estimation (ML, MUSIC, ESPRIT).
- Parametric spectral analysis : Fourier analysis (periodogram, correlogram), Capon spectrum, parametric models (AR, MA, ARMA), Prony’s damped exponential signals modeling, Tufts and Kumaresan approach based on SVD, subspace-based methods (MUSIC, ESPRIT)