Linear Transformation notation

In summary, the conversation discusses the notation T:R^n \implies R^m and how it represents a map between a space of n dimensions to another space of m dimensions. It is clarified that T is not transforming a single number, but rather vectors. Examples are given for when m is smaller, equal, or greater than n, and it is explained that T can also be thought of as a function from ##\mathbb{R}^1## to ##\mathbb{R}^1## or ##\mathbb{R}^2## to ##\mathbb{R}^1##.
  • #1
The Subject
32
0
I'm confused about the notation
[tex]
T:R^n \implies R^m
[/tex]
specifically about m. From my understanding if n=2 then (x1, x2). Are we transforming n=2 to another value m for example (x1, x2, x3)?
 
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  • #2
That is very possible. It is easy to define linear transformations that go from Rn into a subspace of Rm, where m can be smaller, equal, or greater than n:

m smaller than n: (x1, x2) => x1
m equals n: (x1, x2) => (-x1, x1+x2)
m greater than n: (x1, x2) => (x1, x2, x1+x2); another is (x1, x2) => (x1, 0, 0)
 
  • #3
The Subject said:
I'm confused about the notation
[tex]
T:R^n \implies R^m
[/tex]
specifically about m. From my understanding if n=2 then (x1, x2). Are we transforming n=2 to another value m for example (x1, x2, x3)?
That's not the way to think about it. T isn't transforming a single number, like n. It's a map between a space of n dimensions to another space of m dimensions. If n = 2 and m = 3, T is a map from vectors in the plane to vectors in space (three dimensions).

Ordinary functions, which you're probably more familiar with, are maps from ##\mathbb{R}^1## to ##\mathbb{R}^1##. (I added the 1 exponents only for emphasis.) A function of two variables is a map from ##\mathbb{R}^2## to ##\mathbb{R}^1##.
 
  • #4
Okay makes sense. We're transforming vectors.
Mark44 said:
T is a map from vectors in the plane to vectors in space (three dimensions).
I don't feel confident with my understanding of this statement. What does it mean from vectors in the plane
 
  • #5
The Subject said:
Okay makes sense. We're transforming vectors.

I don't feel confident with my understanding of this statement. What does it mean from vectors in the plane
Two-dimensional vectors, like <2, -1>. A vector in space would be, for example, <3, 1, 2>.
 

What is linear transformation notation?

Linear transformation notation is a mathematical representation used to describe transformations of geometric objects or mathematical functions. It is a shorthand way of writing equations that involve variables and coefficients.

What does the notation "T(x)" mean in linear transformation notation?

The notation "T(x)" represents the output of a linear transformation function applied to the input variable "x". It is read as "T of x" or "the transformation of x".

How is a linear transformation represented using mathematical notation?

A linear transformation is represented using the notation "T: V → W", where "T" is the name of the transformation, "V" is the vector space of the input, and "W" is the vector space of the output. This notation indicates that the transformation maps elements from "V" to elements in "W".

What is the difference between a linear transformation and a linear equation?

A linear transformation is a function that maps elements from one vector space to another, while a linear equation is an equation that can be graphed as a straight line. In other words, a linear transformation involves a change in dimensionality, while a linear equation involves a relation between two variables.

How is a linear transformation represented using matrix notation?

A linear transformation can be represented using a matrix notation, where the transformation is represented by a matrix. The columns of the matrix represent the transformation of the basis vectors of the input vector space. This notation is useful for performing calculations involving linear transformations.

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