Autocorrelation

Related lectures (32)

Covers continuous-time stochastic processes and linear systems.

Explores the Fluctuation Dissipation Theorem, covering topics like the Langevin equation and force correlations in high-temperature equilibrium.

Explores stationarity in continuous-time stochastic processes, focusing on autocorrelation and cross-correlation functions.

Explores long memory in time series and ARCH models for financial volatility.

Covers stochastic models for communications and the analysis of random processes in communication systems.

Covers Parseval relations, Fourier series, energy calculation, and correlation in signal processing.

Explores the fundamentals of time series analysis, including stationarity, linear processes, forecasting, and practical aspects.

Covers the estimation and prediction of random signals in linear systems.

Covers the spectral density of continuous-time stochastic processes and its estimation.

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

Introduces spatial dependence, the paradox of classical statistics, and the bias in linear regression.

Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.

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