Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Wiener Process: Definition and Properties
Graph Chatbot
Related lectures (53)
Principal Components: Properties & Applications
Explores principal components, covariance, correlation, choice, and applications in data analysis.
Fourier Transform and Spectral Densities
Covers the Fourier transform, spectral densities, Wiener-Khinchin theorem, and stochastic processes.
Distinct Elements: Count and Hash Functions
Covers counting distinct elements using hash functions and the median trick.
Stochastic Differential Equations
Covers Stochastic Differential Equations, Wiener increment, Ito's lemma, and white noise integration in financial modeling.
Fokker-Planck Equation: Derivations and Applications
Explores the derivation of the Fokker-Planck equation and its applications in stochastic differential equations.
Algorithms & Growth of Functions
Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.
Quantifying Statistical Dependence: Covariance and Correlation
Explores covariance, correlation, and mutual information in quantifying statistical dependence between random variables.
Sub- and Supermartingales: Theory and Applications
Explores sub- and supermartingales, stopping times, and their applications in stochastic processes.
Stochastic Processes: Brownian Motion
Explores Brownian motion, Langevin equations, and stochastic processes in physics.
White Noise Form of the Langevin Equation
Covers the white noise form of the Langevin equation and its applications.
Signal Processing Fundamentals
Log in to Mediaspace to watch this video
Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.
Causal Systems & Transforms: Delay Operator Interpretation
Log in to Mediaspace to watch this video
Covers z Variable as a Delay Operator, realizable systems, probability theory, stochastic processes, and Hilbert Spaces.
Conditional Gaussian Generation
Log in to Mediaspace to watch this video
Explores the generation of multivariate Gaussian distributions and the challenges of factorizing covariance matrices.
Probability and Stochastic Processes: Fundamentals and Applications
Log in to Mediaspace to watch this video
Discusses the fundamentals of probability and stochastic processes, focusing on random variables, their properties, and applications in statistical signal processing.
Stochastic Calculus: Itô's Formula
Log in to Mediaspace to watch this video
Covers Stochastic Calculus, focusing on Itô's Formula, Stochastic Differential Equations, martingale properties, and option pricing.
Stochastic Processes: Stationarity in Continuous Time - Part 2
Log in to Mediaspace to watch this video
Discusses weak-sense stationarity in continuous-time stochastic processes and the calculation of autocorrelation and cross-correlation functions.
Stochastic Calculus: Brownian Motion
Log in to Mediaspace to watch this video
Explores stochastic processes in continuous time, emphasizing Brownian motion and related concepts.
Point Processes: Convergence and Gaussian Processes
Log in to Mediaspace to watch this video
Covers point processes, convergence criteria, Laplace functionals, Gaussian processes, covariance functions, and intrinsic stationarity.
Stochastic Calculus: Integrals and Processes
Log in to Mediaspace to watch this video
Explores stochastic calculus, emphasizing integrals, processes, martingales, and Brownian motion.
Stochastic Models for Communications
Log in to Mediaspace to watch this video
Covers random vectors, stochastic models, functions, matrices, and expectations in communication systems.
Previous
Page 1 of 3
Next