A normed vector space is a pair (V, ‖·‖ ) where V is a vector space and ‖·‖ a norm on V.
We often omit p or ‖·‖ and just write V for a space if it is clear from the context what (semi) norm we are using.
In a more general sense, a vector norm can be taken to be any real-valued vector that satisfies these three properties. The properties 1. and 2. together imply that if and only if x = 0.
A useful variation of the triangle inequality is for any vectors x and y.
This also shows that a vector norm is a continuous function.
dual space W* of W can naturally identified with linear functionals
The question is nonsense. A linear square metre is like a square circle! Linear refers to length or distance in 1-dimensional space while a square metre is a measure of area in 2-dimensional space.
Square yards are a measure of area, i.e. 2-dimensional space, and linear feet are a measure of...well, lines, i.e. 1-dimensional space. One cannot be computed into the other.
There can be linear equations with 1, 2, ... variables. Each of these is different since an equation with n variables belongs to n-dimensional space.
using the function norm(A,x) where A is the matrix/vector that you have to compute the norm for and x can be 1,2,inf, or 'fro' to compute the 1-norm, 2-norm, infinite-norm and frobenius norm respectively.
no -- consider linear map sending entire source space to zero of target space
In linear algebra the norm is the function that assigns a positive length or size to a number. So for example the norm of negative six is six. It is usually denoted with double vertical lines x.
dual space W* of W can naturally identified with linear functionals
The question doesn't make sense, or alternatively it is true by definition. A Hilbert Space is a complete inner product space - complete in the metric induced by the norm defined by the inner product over the space. In other words an inner product space is a vector space with an inner product defined on it. An inner product then defines a norm on the space, and every norm on a space induces a metric. A Hilbert Space is thus also a complete metric space, simply where the metric is induced by the inner product.
It is a vector space with a quasi norm instead of a norm. A quasi norm is a variation of a norm which follows all the norm axioms except for the triangle inequality where we have x+y< or = K(x+y)for some K>1
It depends on what space your in. If its the supremum norm on a function space then just look for the max of the function. If its the euclidean norm then just takes squares, add, take the square root. Whats more interesting is that its often very hard to compute norms. For instance, even computing the norm of a 2x2 matrix is no easy problem if the matrix isn't diagonalizable. Computing the norm of a given operator on a infinite dimensional Hilbert space is very hard indeed...
It tells us how to measure the length of the vectors.
An elevator is not considered a linear object in mathematics. A linear object would usually refer to a one-dimensional space or a straight line, whereas an elevator operates in a three-dimensional space moving vertically.
A linear equation represents a line. A linear inequality represents part of the space on one side (or the other) of the line defined by the corresponding equation.
The question is nonsense. A linear square metre is like a square circle! Linear refers to length or distance in 1-dimensional space while a square metre is a measure of area in 2-dimensional space.
Positive space and negative space
A linear foot has no width, so no matter how many you have of them, you will never cover a 32 x 30 space.