Stochastic process

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Related lectures (32)

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Mean Field Theory: Stochastic Analysis and Applications

Explores classical mean field theory, local interactions, and examples like individual-based SIR models and raindrop formation.

Stochastic Analysis & Random Fields

Covers the outcomes of a virtual seminar on stochastic analysis.

Stochastic Models for Communications

Covers stochastic models for communications and the estimation of correlation functions.

Stochastic Differential Equations

Covers Stochastic Differential Equations, Wiener increment, Ito's lemma, and white noise integration in financial modeling.

Probability and Stochastic Processes: Fundamentals and Applications

Discusses the fundamentals of probability and stochastic processes, focusing on random variables, their properties, and applications in statistical signal processing.

Stochastic Calculus: Foundations and Applications

Explores the foundation of stochastic calculus, emphasizing deterministic and memoryless processes.

Stochastic Integration

Covers stochastic integration and exchange mobility for mathematics students.

Markov Chains: Definition and Examples

Covers the definition and properties of Markov chains, including transition matrix and examples.

Wiener Filter for Discrete-Time Stochastic Processes

Covers the theory and application of the Wiener filter for discrete-time stochastic processes.

Continuous-Time Stochastic Processes: Ergodicity Examples

Covers examples of ergodicity in continuous-time stochastic processes, illustrating concepts such as ergodicity and random processes.