- published: 01 Nov 2015
- views: 925
In mathematics, physics, and engineering, a Euclidean vector (sometimes called a geometric or spatial vector, or—as here—simply a vector) is a geometric object that has magnitude (or length) and direction and can be added to other vectors according to vector algebra. A Euclidean vector is frequently represented by a line segment with a definite direction, or graphically as an arrow, connecting an initial point A with a terminal point B, and denoted by
A vector is what is needed to "carry" the point A to the point B; the Latin word vector means "carrier". It was first used by 18th century astronomers investigating planet rotation around the Sun. The magnitude of the vector is the distance between the two points and the direction refers to the direction of displacement from A to B. Many algebraic operations on real numbers such as addition, subtraction, multiplication, and negation have close analogues for vectors, operations which obey the familiar algebraic laws of commutativity, associativity, and distributivity. These operations and associated laws qualify Euclidean vectors as an example of the more generalized concept of vectors defined simply as elements of a vector space.
Elementary Linear Algebra Lecture 16 - Euclidean Vector Spaces (part 1)
Elementary Linear Algebra Lecture 17 - Euclidean Vector Spaces (part 2)
Elementary Linear Algebra Lecture 18 - Euclidean Vector Spaces (part 3)
Elementary Linear Algebra Lecture 19 - Euclidean Vector Spaces (part 4)
Elementary Linear Algebra Lecture 21 - Euclidean Vector Spaces (part 6)
Lecture 19, Euclidean n-Space, General Vector Spaces
2 1 3 Euclidean Vector Spaces
Euclidean Spaces Lecture 1 Part 2: Vector Algebra
Intermediate Dynamics: Elements of Euclidean Vector Algebra (1 of 29)
Intermediate Dynamics: Elements of Euclidean Vector Calculus (2 of 29)
This video looks at, - Vectors -Linear Combinations 6:40
This video consists of - Norm - Unit vector and normalisation 3:54 - Distance 5:55 - Dot product 6:17
This video covers - Cauchy-Scwarz Inequality - Proof of some identities + The Triangle inequality 6:02 + Triangle inequality for distance 10:48 + Parallelogram equation a 13:20 + Parallelogram equation b 15:35
This video describes how vectors can expressed in matrix form
This video covers, - Projection theorem - Pythogoras theorem revisited 12:49
Reference: http://sameradeeb.srv.ualberta.ca Video production was funded by the University of Alberta Provost's Digital Learning Committee. Thanks to the CTL production team at UoA for their video editing: https://uofa.ualberta.ca/centre-for-teaching-and-learning/about-ctl/people/production-team
We define vectors and describe their algebra, which behaves exactly as matrix algebra.
Recorded live at Cal Poly Pomona during Spring 2015. Note: There was an problem with the camera tripod during this lecture and some scenes required the videographer to hold the camera by hand when recording. This resulted in unsteady video at times. The issue was fixed for future lectures.