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Related lectures (31)
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Spectral Estimation: Periodogram and Tapering
Explores spectral representations, ACVS estimation, and spectral estimation in time series analysis.
Fast Fourier Transform (FFT): Lecture 4
Covers the Fast Fourier Transform (FFT) algorithm, interpolation, filters, image processing, and experimental techniques in TEM and STM.
Time Series: Spectral Analysis and Linear Filtering
Explores spectral analysis, aliasing, and linear filtering in time series data.
Multivariate Time Series and Spectral Representation
Explores multivariate time series analysis, emphasizing spectral representation and estimation methods.
Time Series: Estimation and Spectral Representation
Explores time series estimation, spectral representation, and p-variate analysis in depth.
Laser Spectrum Analysis
Covers laser spectrum measurement methods and the Wiener-Khinchin theorem.
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.
Parseval Relations and Fourier Transform
Covers Parseval relations, Fourier series, energy calculation, and correlation in signal processing.
Continuous-Time Stochastic Processes: Spectral Density
Covers the spectral density of continuous-time stochastic processes and its estimation.