Proving matrix A is linear

In summary, the given information shows that if F is a continuous function on Rn and satisfies the condition F(X+Y) = F(X) + F(Y) for all X and Y in Rn, then A is a linear transformation. This can be shown by considering the fact that a transformation A is linear if A(aX) = aA(X) for any scalar a, and using the hint that rational numbers are dense in the reals.
  • #1
bobbarker
8
0

Homework Statement


Show that if F is continuous on Rn and F(X+Y) = F(X) + F(Y) for all X and Y in Rn, then A is linear. Hint: Rational numbers are dense in the reals.

Homework Equations


A transformation A is linear iff A(X) = (a matrix)
[ a11x1+...+a1nxn ]
[... ... ...]
[ am1x1+...+amnxn ]

The Attempt at a Solution



F(X) = A(X) is continuous and F(X+Y) = A(X+Y) = F(X) + F(Y) = A(X)+A(Y)

I feel like this basically proves itself...since a tranformation A is linear if A(X+Y) = A(X) + A(Y)... I don't understand where the denseness of rational numbers comes in?

Any help is greatly appreciated! :)
 
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  • #2
hi bobbarker! :smile:
bobbarker said:
… a tranformation A is linear if A(X+Y) = A(X) + A(Y)

nooo :redface:

a transformation A is linear if A(aX) = aA(X) for any scalar a :wink:
 

What is a linear matrix?

A linear matrix is a mathematical representation of a linear transformation, which is a function that maps one vector space to another while preserving the structure of the space. In simpler terms, it is a way to express a system of equations using matrices and vectors.

How do I prove that a matrix A is linear?

To prove that a matrix A is linear, you must show that it satisfies two properties: additive and homogeneous. Additive property means that for any two vectors u and v, the transformation of their sum is equal to the sum of their transformations. Homogeneous property means that for any scalar c and vector v, the transformation of cv is equal to c times the transformation of v. If both of these properties hold, then the matrix A is considered linear.

What are some common techniques for proving linearity of a matrix?

One common technique is to use the definition of linearity and plug in values for u and v to see if the additive and homogeneous properties hold. Another technique is to use matrices to represent the transformation and use algebraic properties of matrices to show that the properties hold. Additionally, you can also use examples or counterexamples to demonstrate the linearity of a matrix.

What are some real-world applications of linear matrices?

Linear matrices have many applications in science and engineering, such as in computer graphics, economics, and physics. In computer graphics, linear matrices are used to represent 3D transformations and rotations. In economics, they are used to model systems of equations for supply and demand. In physics, they are used to study systems like electrical circuits and mechanical systems.

What is the difference between a linear and non-linear matrix?

A linear matrix satisfies the properties of additivity and homogeneity, while a non-linear matrix does not. Non-linear matrices can exhibit complex behavior, such as exponential growth or decay, while linear matrices have a more predictable and consistent behavior. Additionally, the solutions to systems of equations represented by linear matrices can be easily calculated, while non-linear systems may require more advanced methods to solve.

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