One more Linear Transformation

In summary, the conversation is about a problem involving a linear transformation from R2 to P1, where the function is defined as f(a,b) = b + a2x. The conditions for a linear transformation are discussed, and it is determined that the second condition is not met due to a mistake in the calculations. The conversation ends with a demonstration of why the two expressions, f(u + v) and f(u) + f(v), are not equal.
  • #1
says
594
12

Homework Statement


I've posted a few of these recently. I have one question about this problem -- hopefully my calculations are correct.

f: R2 to P1, f(a,b)=b+a2x

Is this a linear transformation?

Homework Equations


f(u+v) = f(u) + f(v)
f(cu) = cf(u)

where u and v are vectors in R2 and c is a scalar.

The Attempt at a Solution


let u=(u1,u2)
let v=(v1,v2)

f(u+v) = ((u2+v2) + (u12x+v12x))

f(u) + f(v) = (u2 + u12x) + (v2 + v12x)

So f(u+v) = f(u) + f(v) (First condition met)

c(u1,u2) = (cu1,cu2)

f(cu) = cu2 + cu12x

cf(u) = c(u2 + u12x)
= cu2 + cu12x

Second condition met.

However, my question is -- The question asks is this a linear transformation from R2 to p1. If my calculations are correct, both conditions are met, but the polynomial has a degree of 2, not 1, so it's not a linear transformation from R2 to p1.
 
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  • #2
The squared u1 and v1 will have a c^2 coefficient, not c. So second condition is not met.
if v1 -> c*v1
then v1^2 -> c^2*v1^2
 
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  • #3
says said:

Homework Statement


I've posted a few of these recently. I have one question about this problem -- hopefully my calculations are correct.

f: R2 to P1, f(a,b)=b+a2x

Is this a linear transformation?

Homework Equations


f(u+v) = f(u) + f(v)
f(cu) = cf(u)

where u and v are vectors in R2 and c is a scalar.

The Attempt at a Solution


let u=(u1,u2)
let v=(v1,v2)

f(u+v) = ((u2+v2) + (u12x+v12x))
The way you compute ##f(u+v)## is not correct: in general, ##(u_1+v_1)² \neq {u_1}²+{v_1}²##.
says said:
f(u) + f(v) = (u2 + u12x) + (v2 + v12x)

So f(u+v) = f(u) + f(v) (First condition met)

c(u1,u2) = (cu1,cu2)

f(cu) = cu2 + cu12x
This is not correct, you should have a ##c²{u_1}²x## in the right hand side expression.
says said:
cf(u) = c(u2 + u12x)
= cu2 + cu12x

Second condition met.

However, my question is -- The question asks is this a linear transformation from R2 to p1. If my calculations are correct, both conditions are met, but the polynomial has a degree of 2, not 1, so it's not a linear transformation from R2 to p1.
The polynomial has a degree of 1 in ##x##.
 
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  • #4
I see what you mean with the c2 on the right hand side of the equation, I forgot to put a parenthesis around it (cu12)x

Just looking at the first part now. Thanks for your replies.
 
  • #5
f(u+v) = [(u2+v2)+(u1+v1)2x]

I can see now (with @DuckAmuck's reply) that the second condition is not met.

Oh yes, you are correct with the polynomial having a degree of 1 as well! I got my u,v and x variables mixed up there!

I'm still making a few mistakes, but I'm a lot more confident with these now than I was a couple of days ago.
 
  • #6
says said:
f(u+v) = [(u2+v2)+(u1+v1)2x]
Working that out will show that the first condition isn't met either.

says said:
I'm still making a few mistakes, but I'm a lot more confident with these now than I was a couple of days ago.
The never ending joy of learning. :smile:
 
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  • #7
f(u+v) = [(u2+v2)+(u1+v1)2x]

f(u) + f(v) = u2 + u12x + v2 + v12x

That condition isn't met either! Totally skipped over that one.
 
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  • #8
says said:
f(u+v) = [(u2+v2)+(u1+v1)2x]

f(u) + f(v) = u2 + u12x + v2 + v12x

That condition isn't met either! Totally skipped over that one.
Pretend that you're trying to convince an idiot, and show why the first line above isn't equal to the second line.
 
  • #9
Mark44 said:
Pretend that you're trying to convince an idiot, and show why the first line above isn't equal to the second line.

*Convincing myself*

f(u+v) = [(u2+v2)+(u1+v1)2x]

f(u) + f(v) = u2 + u12x + v2 + v12x

(u1+v1)2 ≠ u12 + v12
 
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  • #10
says said:
*Convincing myself*

f(u+v) = [(u2+v2)+(u1+v1)2x]

f(u) + f(v) = u2 + u12x + v2 + v12x

(u1+v1)2 ≠ u12 + v12
Better:
f(u+v) = (u2+v2)+(u1+v1)2x = ##u_2 + v_2 + (u_1^2 + 2u_1v_1 + v_1^2)x##
f(u) + f(v) = u2 + u12x + v2 + v12x = ##u_2 + v_2 + (u_1^2 + v_1^2)x##
Since ## u_1^2 + v_1^2 \ne u_1^2 + 2u_1v_1 + v_1^2##, if ##u_1 \ne v_1##, then f(u + v) ##\ne## f(u) + f(v)
 
Last edited:
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Related to One more Linear Transformation

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another in a way that preserves the operations of vector addition and scalar multiplication. In simpler terms, it is a way of transforming points in one space to points in another space while maintaining the same shape and structure.

2. How is a linear transformation represented?

A linear transformation can be represented by a matrix, which is a rectangular array of numbers. The dimensions of the matrix correspond to the number of inputs and outputs of the transformation. Alternatively, it can also be represented by a system of linear equations.

3. What are the properties of a linear transformation?

There are three main properties of a linear transformation: 1) it preserves vector addition, meaning that the transformation of the sum of two vectors is equal to the sum of their individual transformations, 2) it preserves scalar multiplication, meaning that the transformation of a vector multiplied by a scalar is equal to the scalar multiplied by the vector's transformation, and 3) it preserves the zero vector, meaning that the transformation of the zero vector is equal to the zero vector.

4. What is the difference between a linear transformation and a nonlinear transformation?

A linear transformation follows the properties mentioned above, while a nonlinear transformation does not. This means that a nonlinear transformation does not preserve vector addition, scalar multiplication, or the zero vector. In other words, the shape and structure of the space being transformed can change with a nonlinear transformation.

5. How are linear transformations used in real-world applications?

Linear transformations have many applications in fields such as physics, engineering, and computer graphics. They are used to model physical systems, such as in the study of fluid dynamics or electrical circuits, as well as in computer graphics to transform 3D objects into 2D images. They are also used in data analysis and machine learning to transform and manipulate data.

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