In order to verify if a given matrix is a Linear Transformation

In summary, the conversation is about showing that a given matrix is closed under addition and multiplication properties, and whether it is possible to show that the vector columns can be spanned in a given R^m. The person being asked is confused about why this needs to be shown and provides an example of a linear transformation to clarify. They also ask for confirmation if they can do this.
  • #1
number0
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0

Homework Statement



I know I am suppose to show that the matrix is closed under addition and multiplication properties, but is it POSSIBLE for me to show that the vector columns can be spanned in the given R^m (assume that the Linear Transformation happens from R^n -> R^m) ?

For example,

[x + y]
[ x ].

This is a linear transformation becausex[1] + y[1]
[1] [0] =span([1] [1])
[1], [0]Can I do this?

Homework Equations


The Attempt at a Solution

 
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  • #2
What you showed was difficult to comprehend, so I added code tags to preserve your formatting.
number0 said:

Homework Statement



I know I am suppose to show that the matrix is closed under addition and multiplication properties, but is it POSSIBLE for me to show that the vector columns can be spanned in the given R^m (assume that the Linear Transformation happens from R^n -> R^m) ?
To clarify your question, yes it's possible to show that the vector columns span Rm, but why do you want to do this?

If you're supposed to show that the matrix represents a linear transformation, show that L(x + y) = L(x) + L(y), and that L(cx) = cL(x), where L is the linear transformation that represents your matrix, x and y are arbitrary vectors in Rn, and c is a scalar.
number0 said:
For example,
Code:
[x + y]
[  x   ].

This is a linear transformation because

Code:
x[1]   + y[1]
  [1]       [0]   =

Code:
span([1]  [1])
       [1], [0]

Can I do this?

Homework Equations





The Attempt at a Solution

 

FAQ: In order to verify if a given matrix is a Linear Transformation

What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another, while preserving the basic structure of the original space. In simpler terms, it is a transformation that maintains the properties of addition and scalar multiplication.

How can I determine if a matrix represents a linear transformation?

To verify if a given matrix is a linear transformation, you can check if it satisfies the two properties of linearity: additivity and homogeneity. Additivity means that the transformation of the sum of two vectors is equal to the sum of the individual transformations, while homogeneity means that the transformation of a scaled vector is equal to the scaled transformation of the original vector.

What is the significance of verifying if a matrix is a linear transformation?

Verifying if a matrix is a linear transformation is important because it allows us to determine if the matrix can be used to efficiently perform various mathematical operations, such as matrix multiplication and finding determinants. It also helps us understand the behavior of the matrix and its relationship to other matrices.

What are some common examples of linear transformations?

Some examples of linear transformations include rotations, reflections, and dilations in geometry, as well as matrix operations such as translation, scaling, and shearing. Additionally, any function that can be expressed as a linear combination of its inputs is considered a linear transformation.

What are the consequences of a matrix not being a linear transformation?

If a matrix does not satisfy the properties of linearity, it cannot be considered a linear transformation. This means that it may not be able to efficiently perform certain mathematical operations and may not have a clear relationship with other matrices. In some cases, it may also lead to incorrect results or inconsistencies in calculations.

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