Singular value decomposition | Abstract algebra | Linear algebra | Matrix theory
In linear algebra, an eigenvector (/ˈaɪɡənˌvɛktər/) or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted by , is the factor by which the eigenvector is scaled. Geometrically, an eigenvector, corresponding to a real nonzero eigenvalue, points in a direction in which it is stretched by the transformation and the eigenvalue is the factor by which it is stretched. If the eigenvalue is negative, the direction is reversed. Loosely speaking, in a multidimensional vector space, the eigenvector is not rotated. (Wikipedia).
Linear Algebra: Ch 3 - Eigenvalues and Eigenvectors (5 of 35) What is an Eigenvector?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain and show (in general) what is and how to find an eigenvector. Next video in this series can be seen at: https://youtu.be/SGJHiuRb4_s
From playlist LINEAR ALGEBRA 3: EIGENVALUES AND EIGENVECTORS
How to Find Eigenvectors Given Eigenvalues
This video explains who to find the eigenvectors that correspond to a given eigenvalue.
From playlist Eigenvalues and Eigenvectors
Find A^n*x Given an Eigenvalue and Eigenvector
This video explains how to use a property of the eigenvector equation to find matrix A to a power times an eigenvector.
From playlist Eigenvalues and Eigenvectors
Properties of Eigenvalues and Eigenvectors: Determining Ax and A(x+y) without A
This video explains how to use eigenvalue and eigenvector properties to determine Ax.
From playlist Eigenvalues and Eigenvectors
10A An Introduction to Eigenvalues and Eigenvectors
A short description of eigenvalues and eigenvectors.
From playlist Linear Algebra
Eigenvalues | Eigenvalues and Eigenvectors
In this video, we work through some example computations of eigenvalues of 2x2 matrices. Including a case where the eigenvalues are complex numbers. We do not discuss any intuition or definition of eigenvalues or eigenvectors, we simply carry out some elementary computations. If you liked
From playlist Linear Algebra
What are Eigenvalues and Eigenvectors?
This video defines and provides examples of eigenvalues and eigenvectors.
From playlist Eigenvalues and Eigenvectors
Linear Algebra: Ch 3 - Eigenvalues and Eigenvectors (22 of 35) Given Eigenvalue, Find Eigenvector=?
Visit http://ilectureonline.com for more math and science lectures! In this video I will find eigenvector=? when given eignevalue lambda2=-1 where A is a 2x2 matrix. Next video in this series can be seen at: https://youtu.be/dN02OkJekZU
From playlist LINEAR ALGEBRA 3: EIGENVALUES AND EIGENVECTORS
Linear Algebra: Ch 3 - Eigenvalues and Eigenvectors (6 of 35) How to Find the Eigenvector
Visit http://ilectureonline.com for more math and science lectures! In this video I will find eigenvectors=? given a 2x2 matrix and 2 eigenvalues. Next video in this series can be seen at: https://youtu.be/EaormewNDpM
From playlist LINEAR ALGEBRA 3: EIGENVALUES AND EIGENVECTORS
Eigenvectors and Eigenvalues — Topic 28 of Machine Learning Foundations
In this video, I leverage colorful illustrations and hands-on code demos in Python to make it intuitive and easy to understand eigenvectors and eigenvalues, concepts that may otherwise be tricky to grasp. There are eight subjects covered comprehensively in the ML Foundations series and th
From playlist Linear Algebra for Machine Learning
21. Eigenvalues and Eigenvectors
MIT 18.06 Linear Algebra, Spring 2005 Instructor: Gilbert Strang View the complete course: http://ocw.mit.edu/18-06S05 YouTube Playlist: https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8 21. Eigenvalues and Eigenvectors License: Creative Commons BY-NC-SA More information at https:
From playlist MIT 18.06 Linear Algebra, Spring 2005
Eigenvectors and Eigenvalues with Jon Krohn
Data scientist Jon Krohn introduces the linear algebra concepts of Eigenvectors and Eigenvalues with a focus on Machine Learning and Python programming. This lesson is an excerpt from “Linear Algebra for Machine Learning LiveLessons” Purchase the entire video course at informit.com/youtub
From playlist Talks and Tutorials
Systems of Differential Equations: Diagonalization and Jordan Canonical Form
It is only possible to perfectly diagonalize certain systems of linear differential equations. For the more general cases, it is possible to "block-diagonalize" the system into what is known as Jordan Canonical Form. This video explores these various options and derives the fully general
From playlist Engineering Math: Differential Equations and Dynamical Systems
22. Diagonalization and Powers of A
MIT 18.06 Linear Algebra, Spring 2005 Instructor: Gilbert Strang View the complete course: http://ocw.mit.edu/18-06S05 YouTube Playlist: https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8 22. Diagonalization and Powers of A License: Creative Commons BY-NC-SA More information at htt
From playlist MIT 18.06 Linear Algebra, Spring 2005
In this video we discuss the concept of eigenvalues and eigenvectors of a matrix. We show that an eigenvector has the property that when it is operated on by the matrix, the resulting output vector is a scaled version of the input vector (it is scaled by the eigenvalue). We discuss how t
From playlist Linear Algebra
Lec 5 | MIT 18.085 Computational Science and Engineering I
Applications to dynamics: eigenvalues of K, solution of Mu'' + Ku = F(t) A more recent version of this course is available at: http://ocw.mit.edu/18-085f08 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 18.085 Computational Science & Engineering I, Fall 2007
(3.5) Types of Behavior of 2D Linear Homogeneous Const Coefficient Systems of ODEs Using Eigenvalues
This lesson explains how to determine the type of of the solution to linear homogeneous constant coefficient systems of ordinary differential equations https://mathispower4u.com
From playlist Differential Equations: Complete Set of Course Videos
5. Eigenvalues and Eigenvectors
MIT 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015 View the complete course: http://ocw.mit.edu/10-34F15 Instructor: James Swan Examples were presented to demonstrate how to find eigenvalues and eigenvectors of a matrix and explain their properties. License: Creative
From playlist MIT 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015
Find an Eigenvalue Given Matrix A and a Eigenvector
This video explains how to find an eigenvalue given a matrix and an eigenvector.
From playlist Eigenvalues and Eigenvectors
4. Eigenvalues and Eigenvectors
MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: https://ocw.mit.edu/18-065S18 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k Professor Strang b
From playlist MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018