Spectral Analysis: Time Series

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Signals and Systems I: Fourier Transform and Spectral Analysis

Explores Fourier series, energy calculation, functional spaces, correlation spectra, and spectral density in signals and systems.

Fourier Transform: Compression and Analysis

Covers the Fourier transform, compression techniques, and spectral analysis of periodic signals.

Spectral Estimation: Periodogram and Tapering

Explores spectral representations, ACVS estimation, and spectral estimation in time series analysis.

Wave Patterns and Spectral Analysis

Explores wave patterns, Fourier transforms, group velocity, and Gaussian spectra in hydrodynamics.

Time Series: Linear Filtering and Spectral Estimation

Explores linear filtering, spectral estimation, and second-order stationarity in time series analysis.

Signals, Frequencies and Bandwidth

Introduces signals, frequencies, and bandwidth, including pure sinusoids, Fourier theory, and spectral representation.

Time Series: Fundamentals and Models

Covers the fundamentals of time series analysis, including models, stationarity, and practical aspects.

Time Series: Structural Modelling and Kalman Filter

Covers structural modelling, Kalman Filter, stationarity, estimation methods, forecasting, and ARCH models in time series.

Spectral & Parametric Estimation: Time Series

Covers spectral estimation techniques like tapering and parametric estimation, emphasizing the importance of AR models and Whittle likelihood in time series analysis.

Power Spectral Density Computation

Covers the computation of power spectral density and the design of communication systems.