Operations with Linear Transformations

In summary, the conversation discusses a potential typo in a book regarding a linear transformation T from a finite-dimensional space U to another space V, and the statement that if dim(U) > dim(V), then Range(T) = V is not possible. The individual providing the summary questions the validity of this statement and provides an example that contradicts it. The summary concludes that this is most likely a typo and not a valid statement.
  • #1
hbweb500
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1

Homework Statement



Let [tex]T:U \rightarrow V[/tex] be a linear transformation, and let U be finite-dimensional. Prove that if dim(U) > dim(V), then Range(T) = V is not possible.

Homework Equations



dim(U) = rank(T) + nullity(T)

The Attempt at a Solution



I almost think there must be a typo in the book. For instance, let U be P4 (the space of polynomials degree 4 and lower), and let V be P2. Let T be the second derivative operator. Then the Range of T is V. This example is even printed earlier in the same book that I got this question from.

Otherwise, I see no reason why the Range(T) couldn't be V. The rank(T) could at most be dim(V), but that is no problem, because the nullity(T) could be anywhere from dim(U) to dim(U)-dim(V).

So, is this a typo? Or (maybe more likely) am I missing something obvious?
 
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  • #2
Let [tex]T:U \rightarrow V[/tex] be a linear transformation, and let U be finite-dimensional. Prove that if dim(U) > dim(V), then Range(T) = V is not possible.

Definitely a typo. It should be <.
 

Related to Operations with Linear Transformations

What is a linear transformation?

A linear transformation is a mathematical function that maps a vector space onto itself, while preserving the structure of the vector space. It can also be thought of as a function that preserves the operations of addition and scalar multiplication.

What are the properties of a linear transformation?

The properties of a linear transformation include:

  • Preserving the zero vector: T(0) = 0
  • Preserving scalar multiplication: T(c*v) = c*T(v)
  • Preserving addition: T(u+v) = T(u) + T(v)

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

A linear transformation satisfies the properties listed above, while a non-linear transformation does not. Additionally, a linear transformation results in a straight-line graph, while a non-linear transformation results in a curved graph.

How can linear transformations be represented?

Linear transformations can be represented in several ways, including:

  • Matrix form: using a matrix to represent the transformation
  • Function notation: using a function to represent the transformation
  • Geometrically: using arrows or diagrams to represent the transformation
  • Algebraically: using equations to represent the transformation

What are some real-world applications of linear transformations?

Linear transformations have many practical applications, including:

  • Computer graphics: to transform and manipulate images
  • Engineering: to solve systems of linear equations
  • Economics: to model relationships between variables
  • Physics: to study transformations of energy and motion
  • Statistics: to analyze data through regression and correlation

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