Difference between orthogonal transformation and linear transformation

In summary: What do you understand by a linear transformation and by an orthogonal transformation?A linear transformation is a transformation that preserves the linearity of a function. An orthogonal transformation is a transformation that preserves the orthogonality of a function.When I start to learn PCA. I find the term "orthogonal transformation" unfamiliar. I google to to find the solution and I get anther unfamiliar term called "linear transformation". So I am unfamiliar with both the terms. I think if Can know the difference between them then it would be very helpful to understand the both term.Do you know what a vector space is? Did you ever study linear algebra?Perhaps I studied Matrix
  • #1
EnglsihLearner
11
1
What is the difference between orthogonal transformation and linear transformation?
 
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  • #2
What do you understand by a linear transformation and by an orthogonal transformation?
 
  • #3
When I start to learner PCA. I find the term "orthogonal transformation" unfamiliar. I google to to find the solution and I get anther unfamiliar term called "linear transformation". So I am unfamiliar with both the terms. I think if Can know the difference between them then it would be very helpful to understand the both term.
 
  • #4
Do you know what a vector space is? Did you ever study linear algebra?
 
  • #5
Perhaps I studied Matrix if it is linear algebra. And I think I understand what is vector space.

Vector space:
http://en.wikipedia.org/wiki/Vector_space

Is it sufficient?

I got the definition of both terms by wikipedia. But I don't understand clearly.
 
  • #6
You should probably study linear algebra if you really want to grasp this.

I'll explain it for Euclidean spaces. A function ##T:\mathbb{R}^n\rightarrow \mathbb{R}^m## is called linear if the following two properties are satisfied

1) ##T(\mathbf{x} + \mathbf{y}) = T(\mathbf{x}) + T(\mathbf{y})## for ##\mathbf{x},\mathbf{y}\in \mathbb{R}^n##.
2) ##T(\lambda\mathbf{x}) = \lambda T(\mathbf{x})## for ##\mathbf{x}\in \mathbb{R}^n## and ##\lambda\in \mathbb{R}##.

Now, an orthogonal transformation is a linear transformation if it preserves the inner product. On ##\mathbb{R}^n## you have the inner product

[tex]\mathbf{x}\cdot \mathbf{y} = x_1 y_1 + ... + x_n y_n[/tex]

Thus an orthogonal transformation satisfies ##T(\mathbf{x}) \cdot T(\mathbf{y}) = \mathbf{x} \cdot \mathbf{y}## for each ##\mathbf{x},\mathbf{y}\in \mathbb{R}^n##. Note that by definition an orthogonal transformation is linear.
 
  • #7
Thanks.
I will back again after reading linear algebra. I am working on a topic called ECG(Electrocardiogram). I must understand PCA(Principal Component Analysis) to grasp ECG.I hope with your help I will be able to understand PCA.

Thanks again.
 
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  • #9
EnglsihLearner said:
What is the difference between orthogonal transformation and linear transformation?

In 2D, an intuitive way to look at it is that linear transformations preserve parallelograms. Othogonal transformations preserve rectangles.

For example in 2D plane, one property of a linear transformation is that it preserves the origin of the plane and preserves those parallelograms that have one vertex at the origin. For example, it would be OK for a linear transformation to send the rectangle (0,0)(2,0),(2,1)(0,1) to the parallelogram with vertices (0,0),(2,0),(3,2)(1,2). An orthogonal transformation preserves rectangles. So it will not transform a rectangle into a non-rectangular parallelogram. For example, a rotation of the plane by 30 degrees about the origin preserves such rectangles. The rotation also preserves parallelograms, so it is both a linear tranformation and an orthogonal transformation.
 
  • #10
Orthogonal transformation [itex]\subset[/itex] Linear transformation
 

What is the difference between orthogonal transformation and linear transformation?

Orthogonal transformation is a type of linear transformation that preserves angles and distances between vectors, while linear transformation refers to a change in the position or orientation of a vector.

How do you determine if a transformation is orthogonal or linear?

A transformation is orthogonal if the dot product of two vectors is equal to the dot product of their transformed vectors. A transformation is linear if it follows the properties of linearity, such as preserving scalar multiplication and addition.

Can a transformation be both orthogonal and linear?

Yes, a transformation can be both orthogonal and linear. This means that it preserves both angles and distances, while also following the properties of linearity.

What are some examples of orthogonal transformations?

Some examples of orthogonal transformations include rotations, reflections, and the identity transformation.

How are orthogonal and linear transformations used in real life?

Orthogonal transformations are commonly used in computer graphics to rotate or reflect images. Linear transformations are used in various fields, such as engineering and physics, to model changes in variables or systems.

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