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Lecture
Gradient, divergence
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Related lectures (31)
Untitled
Vector Analysis: Scalar Fields
Covers the analysis of scalar fields, including divergence, gradient, and Laplacian.
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Introduces tensor transformations, rotation matrices, and differential operators in mechanics.
Continuity Equations: Internal Entropy Production
Explores continuity equations and internal entropy production in various coordinate systems, emphasizing scalar functions and vector quantities.
Deformable Bodies: Stress Tensors and Divergence Theorem
Explores stress tensors and the divergence theorem in deformable bodies through examples and demonstrations.
Spherical Coordinates: Conversion and Applications
Covers the conversion and applications of spherical coordinates in mathematical and physical contexts.
Introduction: Mathematical background
Covers basics of modeling for micro/nano devices and emphasizes the importance of computational thinking in understanding and improving device design.
Vector Fields: Gradient and Divergence
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Covers vector fields, gradient, divergence, heat flux, and stress tensors.
Divergence Theorem: Green Identities in R²
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Explores the divergence theorem and corollaries related to Green identities in the plane, demonstrating their application through examples.
Curve Integrals of Vector Fields
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Explores curve integrals of vector fields, emphasizing energy considerations for motion against or with wind, and introduces unit tangent and unit normal vectors.
Differential Operators: Theorems and Proofs
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Covers the concept of differential operators and presents theorems and proofs related to scalar and vector fields.
Divergence of Vector Fields
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Explores divergence of vector fields, rotational definitions, and integral derivation applications.
Vector Calculus Review: Maxwell Equations
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Covers a review of vector calculus and the Maxwell equations in electromagnetism.
Differential Operators: Gradient and Divergence
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Introduces differential operators, gradient, and divergence in vector fields.
Curve Integrals: Gauss/Green Theorem
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Explores the application of the Gauss/Green theorem to calculate curve integrals along simple closed curves.
Understanding Positive and Negative Orientation in Curves
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Explores positive and negative orientation in curves, emphasizing their impact on tangent and normal vectors.
Neural networks under SGD
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Explores the optimization of neural networks using Stochastic Gradient Descent (SGD) and the concept of dual risk versus empirical risk.
Surface Integrals, Divergence Theorem and Stocks' Theorem
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Covers surface integrals, the divergence theorem, and Stocks' theorem through examples and analogies.
Surface Integrals: Parameterization and Divergence Theorem
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Explores surface integrals using parameterization and the divergence theorem, with practical examples included.
Divergence Explained: Lightboard 2-4
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Explores how sources and sinks affect the divergence of vector fields.
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