How can I use the given linear transformation to determine f(x,y)?

In summary, f is a linear transformation that has the property that f(\alpha u+ \beta v)= \alpha fu+ \beta fv where \alpha and \beta are scalars and u and v are vectors.
  • #1
negation
818
0

Homework Statement



Say if f is a linear transformation from R2 to R3 with f(1,0) = (1,2,3) and f(0,1) = (0,-1,2).
Determine f(x,y).


The Attempt at a Solution




I understand the theorem on linear transformation and bases but unsure as to how I should apply it in practice. Should I be performing the linear transformation test? But the question has already specified that f is a linear transformation.

Edit: {u1,u2,u3...un} is a basis for Rn and {t1,t2,t3...tn} is a basis for Rm
then there is a unique linear transformation such that f maps (u1) to t1: f(u1) = t1

This can be expressed as f(u1) = t1, f(u2) = t2, f(u3) = t3...f(un) = tn

f:R2 →R3

f(e1) = (1,2,3)
∴f(1,0) = (1,2,3)
∴f(1) = 1, f(0) = 2

f(e2) = (0,-1,2)
∴f(0,1) = (0,-1,2)
∴f(0) = 0, f(1) = -1
 
Last edited:
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  • #2
A linear transformation, f, has the property that [itex]f(\alpha u+ \beta v)= \alpha fu+ \beta fv[/itex] where [itex]\alpha[/itex] and [itex]\beta[/itex] are scalars and u and v are vectors.

You know f(0,1) and f(1, 0) so given any (x, y), apply f to x(1, 0)+ y(0, 1).
 
  • #3
negation said:

Homework Statement



Say if f is a linear transformation from R2 to R3 with f(1,0) = (1,2,3) and f(0,1) = (0,-1,2).
Determine f(x,y).


The Attempt at a Solution




I understand the theorem on linear transformation and bases but unsure as to how I should apply it in practice. Should I be performing the linear transformation test? But the question has already specified that f is a linear transformation.

Can you write [itex](x,y) \in \mathbb{R}^2[/itex] as a linear combination of vectors for which you are given the value of [itex]f[/itex]?
 
  • #4
HallsofIvy said:
A linear transformation, f, has the property that [itex]f(\alpha u+ \beta v)= \alpha fu+ \beta fv[/itex] where [itex]\alpha[/itex] and [itex]\beta[/itex] are scalars and u and v are vectors.

You know f(0,1) and f(1, 0) so given any (x, y), apply f to x(1, 0)+ y(0, 1).

Hi halls, I've added some content to the OP.
 
  • #5
HallsofIvy said:
A linear transformation, f, has the property that [itex]f(\alpha u+ \beta v)= \alpha fu+ \beta fv[/itex] where [itex]\alpha[/itex] and [itex]\beta[/itex] are scalars and u and v are vectors.

You know f(0,1) and f(1, 0) so given any (x, y), apply f to x(1, 0)+ y(0, 1).

pasmith said:
Can you write [itex](x,y) \in \mathbb{R}^2[/itex] as a linear combination of vectors for which you are given the value of [itex]f[/itex]?
Suppose u = (e1) and v = (e2)
f(u) = (1,2,3) and f(v) = 0,-1,2)

f(λ1u + λ2v) = λ1f(u) + λ2f(v)
= λ1 f(1,0) + λ2 f(0,1)
∴λ1(1,2,3) + λ2 (0,-1,2) = λ1(1,2,3) + λ2(0,-1,2)

and if I am given λ1 and λ2 I can find a vector as a linear combination of
λ1(1,2,3) + λ2(0,-1,2).
 

What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another while preserving the properties of vector addition and scalar multiplication. In other words, it is a transformation that maintains the shape and orientation of the original vector space.

What are the key properties of a linear transformation?

The key properties of a linear transformation include:

  • Preservation of vector addition: This means that the sum of two vectors in the original vector space will be equal to the sum of their corresponding transformed vectors in the new vector space.
  • Preservation of scalar multiplication: This means that multiplying a vector by a scalar in the original vector space will result in the same scalar multiple of the transformed vector in the new vector space.
  • Preservation of the origin: This means that the origin (zero vector) in the original vector space will be mapped to the origin in the new vector space.

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

The main difference between a linear and non-linear transformation is that a linear transformation preserves the properties of vector addition and scalar multiplication, while a non-linear transformation does not. This means that a non-linear transformation will result in a change in shape or orientation of the original vector space.

What are the common types of linear transformations?

Some common types of linear transformations include:

  • Rotation: This transformation rotates the points in a vector space around a fixed point.
  • Reflection: This transformation reflects points across a given line or plane.
  • Scaling: This transformation increases or decreases the size of points in a vector space.
  • Shearing: This transformation skews the points in a vector space along a given axis.
  • Translation: This transformation moves points in a vector space by a given distance in a given direction.

How is a linear transformation represented mathematically?

A linear transformation can be represented mathematically using a transformation matrix. This matrix is constructed using the coefficients of the linear transformation's equations and is used to map the original vector space to the new vector space.

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