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.
Covers statistical signal processing tools for wireless communications, including spread spectrum, spectral analysis, ultra-wide band communications, and heart rate variability analysis.
Covers spectral estimation techniques like tapering and parametric estimation, emphasizing the importance of AR models and Whittle likelihood in time series analysis.
