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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the concepts of linear prediction and estimation in signal processing, focusing on optimal filters, Wiener filters, random signals, stationarity, ergodicity, and linear filtering. It also discusses random processes, stochastic processes, probability density, joint probability density, autocorrelation, autocovariance, intercorrelation, intercovariance, power spectral density, and Fourier transform.