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A unit vector is often denoted by a lowercase letter with a circumflex, or "hat", as in ^ (pronounced "v-hat"). The normalized vector û of a non-zero vector u is the unit vector in the direction of u, i.e., ^ = ‖ ‖ where ‖u‖ is the norm (or length) of u. [1] [2] The term normalized vector is sometimes used as a synonym for unit vector.
A reflection about a line or plane that does not go through the origin is not a linear transformation — it is an affine transformation — as a 4×4 affine transformation matrix, it can be expressed as follows (assuming the normal is a unit vector): [′ ′ ′] = [] [] where = for some point on the plane, or equivalently, + + + =.
The matrix and the vector can be represented with respect to a right-handed or left-handed coordinate system. Throughout the article, we assumed a right-handed orientation, unless otherwise specified. Vectors or forms The vector space has a dual space of linear forms, and the matrix can act on either vectors or forms.
Matrices can be used to compactly write and work with multiple linear equations, that is, systems of linear equations. For example, if A is an m×n matrix, x designates a column vector (that is, n×1-matrix) of n variables x 1, x 2, ..., x n, and b is an m×1-column vector, then the matrix equation =
ρ is the length of the vector projected onto the xy-plane, φ is the angle between the projection of the vector onto the xy-plane (i.e. ρ) and the positive x-axis (0 ≤ φ < 2π), z is the regular z-coordinate. (ρ, φ, z) is given in Cartesian coordinates by:
Vector geometry of Rodrigues' rotation formula, as well as the decomposition into parallel and perpendicular components. Let k be a unit vector defining a rotation axis, and let v be any vector to rotate about k by angle θ (right hand rule, anticlockwise in the figure), producing the rotated vector .
A three-dimensional vector can be specified in the following form, using unit vector notation: = ^ + ȷ ^ + ^ where v x, v y, and v z are the scalar components of v. Scalar components may be positive or negative; the absolute value of a scalar component is its magnitude.
A linear combination of v 1 and v 2 is any vector of the form [] + [] = [] The set of all such vectors is the column space of A. In this case, the column space is precisely the set of vectors ( x , y , z ) ∈ R 3 satisfying the equation z = 2 x (using Cartesian coordinates , this set is a plane through the origin in three-dimensional space ).