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Related lectures (29)
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Curve Integrals: Gauss/Green Theorem
Explores the application of the Gauss/Green theorem to calculate curve integrals along simple closed curves.
Unconstrained Optimization Theory
Explores unconstrained optimization theory, covering global and local minima, convexity, and gradient concepts.
Hitting Probabilities: Markov Chains
Covers hitting probabilities in Markov chains with disjoint subsets, the function h(i), theorems, proofs, and expected time to hit calculations.
Derivatives and Limits: Generalization and Indeterminacy
Covers the generalization of the TAF theorem, lateral derivatives, limits of derivatives, and indeterminacy.
Boolean Algebra: Properties and Optimization
Covers Boolean algebra properties, optimization techniques, and the importance of valid groups in Karnaugh maps.
Harmonic Forms: Main Theorem
Explores harmonic forms on Riemann surfaces and the uniqueness of solutions to harmonic equations.
Maximization Principle for Elliptic Equations
Explores the maximization principle for elliptic equations and the uniqueness of solutions.
Networked Control Systems: Consensus and Laplacian Flow
Explores the Laplacian flow and achieving consensus in networked control systems through examples and theorems.
Lower Bound on Total Variation Distance
Explores the lower bound on total variation distance in Markov chains and its implications on mixing time.
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