Simple Linear Transformation: Proving Linearity with (1,1) Vectors

In summary, the conversation discusses whether the function f(x,y) = |x+y| is a linear transformation from R^2 to R^1. One person argues that it is not linear, while the other person suggests a counterexample to demonstrate that it does not preserve addition. They then discuss ways to prove or disprove the linearity of the function without using trial and error.
  • #1
negation
818
0

Homework Statement



f(x,y) -> |x+y|



The Attempt at a Solution



The answer is that the above transformation is not linear but my working shows otherwise.

Here's my go:

let u = (1,1) and v = (1,1)

f(u) = f(1,1) = 2

f(v) = f(1,1) = 2

f(u) + f(v) = 4

f(u+v) = f(2,2) = 4

f(u+v) = f(u) + f(v)

So a linear transformation exists.
 
Physics news on Phys.org
  • #2
negation said:

Homework Statement



f(x,y) -> |x+y|



The Attempt at a Solution



The answer is

The answer to what? You haven't stated a question.

that the above transformation is not linear but my working shows otherwise.

Here's my go:

let u = (1,1) and v = (1,1)

f(u) = f(1,1) = 2

f(v) = f(1,1) = 2

f(u) + f(v) = 4

f(u+v) = f(2,2) = 4

f(u+v) = f(u) + f(v)

So a linear transformation exists.

So if it works for those two u and v values, it works for all of them eh?
 
  • #3
LCKurtz said:
The answer to what? You haven't stated a question.



So if it works for those two u and v values, it works for all of them eh?



Woops, I submitted the thread too fast.

The question asks if the function is a linear transformation.

Not necessarily. How should I demonstrate? counter example?

Edit:

Things are different should I allow u = (1,0) and v = (-1,0)

then,

f(u) = 1 and f(v) = 1, then, f(u) + f(v) = 2

but f((u+v)) = f((1-1,0+0)) = f(0,0) = 0
 
  • #4
negation said:
Things are different should I allow u = (1,0) and v = (-1,0)

then,

f(u) = 1 and f(v) = 1, then, f(u) + f(v) = 2

but f((u+v)) = f((1-1,0+0)) = f(0,0) = 0

so your conclusion is...

That's the right idea.
 
  • #5
LCKurtz said:
so your conclusion is...

That's the right idea.

They do not preserve addition.

The value for u and v was randomly pluck. It is obvious that in an examination, trial and error is the last thing I want to assume.

Would you mind shedding some light how I should, without trial and error, arrive at the value for u and v such that they satisfy the condition?
 
  • #6
negation said:
They do not preserve addition.

The value for u and v was randomly pluck. It is obvious that in an examination, trial and error is the last thing I want to assume.

Would you mind shedding some light how I should, without trial and error, arrive at the value for u and v such that they satisfy the condition?

You should start by writing the general thing you are trying to prove or disprove. In your example it was whether ##f(x,y)=|x+y|## is a linear transformation from ##R^2\rightarrow R^1##. So you are checking whether or not if ##u=(a,b)## and ##v = (c,d)## does ##f(u+v)=f(u)+f(v)##. Since ##u+v = (a+c,b+d)## this would mean ##|(a+b)+(c+d)| = |a+b|+|c+d|##.

You need to do that before you start trying to solve the problem, and this is a step that you are routinely skipping. Once you have it clear what you are proving or disproving you can usually tell whether it is an identity or not just by looking at it. You will be able to see the algebra to make it work or find numbers that show it doesn't work. Once you really understand the concept of "linear" they will usually be easy to tell.
 

FAQ: Simple Linear Transformation: Proving Linearity with (1,1) Vectors

What is a simple linear transformation?

A simple linear transformation is a mathematical function that maps a set of data points from one coordinate system to another, while preserving the linearity of the data. This means that the relationship between the data points remains the same after the transformation.

What is the purpose of a simple linear transformation?

The purpose of a simple linear transformation is to simplify and analyze data by transforming it into a more manageable form. This can help identify patterns and relationships between variables, and make it easier to interpret the data.

What are the key components of a simple linear transformation?

The key components of a simple linear transformation are the input variables, the transformation function, and the output variables. The input variables are the data points that are being transformed, the transformation function is the mathematical operation that is applied to the data, and the output variables are the resulting transformed data points.

What is an example of a simple linear transformation?

An example of a simple linear transformation is converting temperature measurements from Fahrenheit to Celsius. The input variables are the temperature readings in Fahrenheit, the transformation function is (F-32) x 5/9, and the output variables are the temperature readings in Celsius.

How is a simple linear transformation different from a complex linear transformation?

A simple linear transformation involves only one input variable and one output variable, while a complex linear transformation involves multiple input variables and multiple output variables. Additionally, a simple linear transformation preserves the linearity of the data, while a complex linear transformation may involve more complex mathematical operations that do not preserve linearity.

Back
Top