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Concept

Wiener process

Related lectures (32)

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Covers the Fourier transform, spectral densities, Wiener-Khinchin theorem, and stochastic processes.

Explores Brownian motion, Langevin equations, and stochastic processes in physics.

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Explains the martingale convergence theorem and its applications in probability theory.

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Explores martingale convergence, discussing the conditions for convergence and variance in martingales.

Covers Doob's decomposition theorem for submartingales and explores Brownian motion properties, quadratic variation, and continuous martingales.

Explores the generation of multivariate Gaussian distributions and the challenges of factorizing covariance matrices.

Explains the definition and properties of the Wiener process, focusing on its covariance function and continuous paths.