'Vector spaces' diaporamas de présentation

Objective

Review Matrices and Vectors. Objective. To provide background material in support of topics in Digital Image Processing that are based on matrices and/or vectors. Review: Matrices and Vectors. Some Definitions.

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Chapter 4 General Vector Spaces

Linear Algebra. Chapter 4 General Vector Spaces. ???? ????? ???. 4.1 General Vector Spaces and Subspaces.

2.67k views • 99 slides

Presented by : Erik Cox, Shannon Hintzman, Mike Miller, Jacquie Otto,

947 views • 79 slides

Math Foundations of CG

Math Foundations of CG. Outline. Abstract spaces: objects and operations Field of real numbers R Vector space over R Euclidean spaces Affine spaces Affine combinations Convex combinations Frames Affine maps Euclidean spaces Read: angel, Appendices B and C, Ch 4.1-4.3. Geometric ADTs.

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Lecture 6 Eigenvalue and Vector Space

967 views • 55 slides

Quantum Computing

Quantum Computing. Lecture on Linear Algebra. Sources: Angela Antoniu , Bulitko, Rezania, Chuang, Nielsen. Introduction to Quantum Mechanics. This can be found in Marinescu and in Chuang and Nielsen Objective To introduce all of the fundamental principles of Quantum mechanics

1.08k views • 52 slides

THE MATHEMATICS OF QUANTUM MECHANICS

737 views • 43 slides

Matrices

Matrices. COMM2M Harry R. Erwin, PhD University of Sunderland. Basic Concepts. Vector space Linear transformation. Resources. Korevaar, J., 1968, Mathematical Methods, Academic Press. Vector Space.

516 views • 41 slides

Review of Linear Algebra

597 views • 34 slides

Objective

Review Matrices and Vectors. Objective. To provide background material in support of topics in Digital Image Processing that are based on matrices and/or vectors. Review: Matrices and Vectors. Some Definitions.

493 views • 32 slides

Objective

Review Matrices and Vectors. Objective. To provide background material in support of topics in Digital Image Processing that are based on matrices and/or vectors. Some Definitions.

478 views • 32 slides

A Brief Survey of Quantum Computing

A Brief Survey of Quantum Computing. Igor Markov http://eecs.umich.edu/~imarkov. Outline. A Brief History of Quantum Computing Background in Mathematics and Quantum Mechanics What Makes Quantum Computing Work? read/write ops for quantum storage

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The Mathematics of Information Retrieval

The Mathematics of Information Retrieval. 11/21/2005 Presented by Jeremy Chapman , Grant Gelven and Ben Lakin. Acknowledgments. This presentation is based on the following paper:

352 views • 23 slides

Linear algebra: matrix Eigen-value Problems

Linear algebra: matrix Eigen-value Problems. Eng. Hassan S. Migdadi. Part 3. Eigenvalue Problems. Eigenvalues and eigenvectors Vector spaces Linear transformations Matrix diagonalization. The Eigenvalue Problem. Consider a n x n matrix A Vector equation: Ax = l x

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5.1 Orthogonal Projections

817 views • 17 slides

Orthogonal Functions and Fourier Series

Orthogonal Functions and Fourier Series. Vector Spaces. Set of vectors Operations on vectors and scalars Vector addition: v 1 + v 2 = v 3 Scalar multiplication: s v 1 = v 2 Linear combinations: Closed under these operations Linear independence Basis Dimension. Vector Spaces.

707 views • 16 slides

Orthogonal Functions and Fourier Series

Orthogonal Functions and Fourier Series. Vector Spaces. Set of vectors Operations on vectors and scalars Vector addition: v 1 + v 2 = v 3 Scalar multiplication: s v 1 = v 2 Linear combinations: Closed under these operations Linear independence Basis Dimension. Vector Spaces.

743 views • 16 slides

Time-reversal and MUSIC

Time-reversal and MUSIC. Anthony J. Devaney Department of Electrical and Computer Engineering Northeastern University Boston, MA 02115 email: tonydev2@aol.com. Review of time-reversal Discussion of Vector Spaces Incorporation of MUSIC Computer Simulations. System Configuration.

404 views • 16 slides

Basics of Linear Algebra

Basics of Linear Algebra. A review?. Matrix. Mathematical term essentially corresponding to an array An arrangement of numbers into rows and columns. Each row is the same length Each column is the same length Usually, we specify a position in the matrix as row, column. Vector.

605 views • 14 slides

The SYMBoL Project

Enhancing the second year experience for undergraduate mathematicians. The SYMBoL Project. http://sym.lboro.ac.uk/. 18 April 2013 Liverpool John Moores University. Francis Duah f.k.duah@lboro.ac.uk , Loughborough University. Reasons for undertaking the project.

201 views • 6 slides