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Lecture
Bases and Dimension
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Related lectures (34)
Vector Spaces and Linear Applications
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Covers vector spaces, subspaces, kernel, image, linear independence, and bases in linear algebra.
Linear Algebra in Dirac Notation
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Covers linear algebra in Dirac notation, focusing on vector spaces and quantum bits.
Linear Algebra: Change of Basis
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Covers the concept of changing bases in linear algebra, emphasizing the importance of understanding the process for various situations.
Orthogonal Bases in R^2
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Explains orthogonal bases in R^2 and how to perform orthogonal projections.
Linear Algebra: Applications and Bases
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Explores unique solutions, linear dependence, canonical bases, and linear maps in linear algebra.
Linear Applications: Basis and Independence
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Covers linear independence, bases of vectors, and solving systems using matrices.
Steinitz Lemma and Cycles
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Explores the Steinitz Lemma and the concept of cycles in linear algebra.
Algebraic Varieties in Linear Algebra
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Explores algebraic varieties in linear algebra, focusing on their nature, determinants, irreducibility, prime properties, and geometric representation theory.
What is a (sub)manifold
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Introduces the concept of a submanifold in a linear space, defining it as a set smoothly embedded in the space.
Linear Transformations: Injective and Surjective
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Explores injective and surjective linear transformations, kernel, image, and matrix operations.
Single-Phase Sinusoidal Circuits
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Covers peak, mean, and rms values, average power, phase advance, and sinusoidal circuits.
Partial Differential Equations: Viscoelastic Materials
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Explores the application of PDEs in viscoelastic materials and materials science.
Gram-Schmidt Process
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Introduces the Gram-Schmidt orthogonalization process to find orthogonal bases for vector subspaces.
Multilinear Forms: Definitions and Properties
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Covers the definition and properties of multilinear forms, emphasizing linearity and applications in mathematics.
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