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Related lectures (28)
Vector Spaces: Properties and Operations
Covers the properties and operations of vector spaces, including addition and scalar multiplication.
Normed Spaces
Covers normed spaces, dual spaces, Banach spaces, Hilbert spaces, weak and strong convergence, reflexive spaces, and the Hahn-Banach theorem.
Orthogonality and Subspace Relations
Explores orthogonality between vectors and subspaces, demonstrating practical implications in matrix operations.
Polynomials: Operations and Properties
Explores polynomial operations, properties, and subspaces in vector spaces.
Linear Algebra: Abstract Concepts
Introduces abstract concepts in linear algebra, focusing on operations with vectors and matrices.
Linear Operators: Boundedness and Spaces
Explores linear operators, boundedness, and vector spaces with a focus on verifying bounded aspects.
Orthogonality and Projection
Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.
Matrix Operations: Linear Systems and Solutions
Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.
Crash Course on Quantum Mechanics
Offers a crash course on quantum mechanics, covering vector spaces, superposition, observables, and self-adjoint operators.
Crash Course on Quantum Mechanics
Covers fundamental concepts in quantum mechanics, including vector spaces, superposition, observables, and inner product.
Orthogonal Vectors and Projections
Covers scalar products, orthogonal vectors, norms, and projections in vector spaces, emphasizing orthonormal families of vectors.
Linear Independence and Bases in Vector Spaces
Explains linear independence, bases, and dimension in vector spaces, including the importance of the order of vectors in a basis.
Principles of Quantum Physics
Covers the principles of quantum physics, focusing on tensor product spaces and entangled vectors.
Properties of Weak Derivatives
Explores weak derivatives in Sobolev spaces, discussing their properties and uniqueness.
Orthogonality and Least Squares Methods
Explores orthogonality, norms, and distances in vector spaces for solving linear systems.
Vector Spaces: Definitions and Properties
Covers the definitions and properties of vector spaces, including axioms and examples.
Function Spaces and Hilbert Spaces
Introduces function spaces and Hilbert spaces, discussing inner product spaces and the importance of completeness in Hilbert spaces.
Linear Combinations and Vector Spaces
Introduces linear combinations in vector spaces, operations, and polynomials of degree 2.
Dirac's Notation, Tensor Product
Covers Dirac's notation in linear algebra and the tensor product concept in Hilbert spaces.
Orthogonality and Least Squares
Introduces orthogonality between vectors, angles, and orthogonal complement properties in vector spaces.
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