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Related lectures (31)

Explores the properties and applications of Cayley graphs in group theory and network analysis.

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Explores different types of noise in devices and circuits, including interference noise, inherent noise, and random signals.

Covers the concept of sparse regression and the use of Gaussian additive noise in the context of MAP estimator and regularization.

Explains the proof of the ergodic theorem and the concept of positive-recurrence in Markov chains.

Explores the coupling of Markov chains and the proof of the ergodic theorem, emphasizing distribution convergence and chain properties.

Discusses approximation by smooth functions and the convergence of function sequences in normed vector spaces.

Explores the physics of electrophoresis for protein characterization, covering Native Gel, SDS-PAGE, and 2D Gel.

Explores Markov chains and their applications in algorithms, focusing on user impatience and faithful sample generation.

Covers the theory of Markov chains, focusing on reversible chains and detailed balance.

Covers the theory and applications of Markov chains in modeling random phenomena and decision-making under uncertainty.

Explores noise and offset reduction techniques in analog circuits, focusing on Autozero and Chopper Stabilization.

Covers Markov chains, coupled chains, and their applications, emphasizing the importance of irreducibility.

Covers the interpretation of the Lindblad equation and its unitary part in quantum gases.

Covers Markov chains and their applications in algorithms, focusing on Markov Chain Monte Carlo sampling and the Metropolis-Hastings algorithm.

Explores the properties and structure of gels, including sol-gel processes and the formation of different types of gels.

Explores electrical metrology, covering random variables, noise sources, and their impact on electronic devices.