Explores the stochastic properties and modelling of time series, covering autocovariance, stationarity, spectral density, estimation, forecasting, ARCH models, and multivariate modelling.
Covers the stochastic properties of time series, stationarity, autocovariance, special stochastic processes, spectral density, digital filters, estimation techniques, model checking, forecasting, and advanced models.
Explores linear prediction, optimal filters, random signals, stationarity, autocorrelation, power spectral density, and Fourier transform in signal processing.
Explores statistical signal processing tools for wireless communications, including spectral estimation and signal detection, classification, and adaptive filtering.