Skip over navigation

Vector Multiplication

Terms

Introduction to Vector Multiplication

The Dot Product

Direction  -  The direction in which a 2D-vector points can be characterized by a single angle; for 3D-vectors two angles are needed.
Euclidean Space  -  The name given to all finite-dimensional spaces obtained by taking Cartesian products of the real numbers R . They are denoted by R n for n = 1, 2, 3... .
Magnitude  -  The magnitude of a vector is its length, or distance from the origin.
Projection  -  The projection of a vector in a particular direction is its "shadow" along that direction. If u is a unit vector, the projection of a vector v in the direction of u is given by a new vector which points in the direction of u and whose magnitude is v·u : i.e. the projection of v in the direction of u is precisely (v·u)u .
Right-hand rule  -  This is the standard convention chosen when defining the cross product between two vectors. It states that i×j = k , instead of -k , even though both options are equally valid. Once this convention has been chosen, there is no longer any ambiguity about whether the cross product between two vectors points upwards or downwards. (Before this we only knew it had to point in a direction perpendicular to the plane of the original two vectors).
Rotational invariance  -  A vector quantity (such as the dot product or the cross product) is rotationally invariant if its value remains the same under a rotation of its input vectors. Both the dot product and the cross product are rotationally invariant, while vector addition and scalar multiplication, in general, are not.
Scalar  -  An ordinary number; whereas vectors have direction and magnitude, scalars have only magnitude. The scalars we will be dealing with will all be real numbers, but other kinds of numbers can also be scalars. 5 miles represents a scalar.
Unit vector  -  A vector whose length is one. The unit vectors which point in the x -, y -, and z -directions in typical 3-dimensional space are usually denoted by i , j , and k , respectively.
Vector  -  A two-dimensional vector is an ordered pair (a, b) of numbers; a three-dimensional vector is an ordered triplet (a, b, c) . In other words, points in the plane or in three-dimensional space are vectors. These kinds of vectors can also be described as having direction and magnitude: 5 miles to the east represents a vector.
Vector Space  -  A set that is closed under addition and scalar multiplication. Examples of vector spaces include the Euclidean plane R 2 and ordinary three- dimensional space R 3 .

Follow Us