Difference between linear and nonlinear transformation

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Linear transformations are defined by their adherence to linearity conditions, specifically T(x+y)=T(x)+T(y) and T(ax)=aT(x), without the necessity of being one-to-one. Nonlinear transformations do not follow these linearity conditions and can also be one-to-one. The confusion arises from the misconception that linear transformations must be one-to-one, which is not true; many linear transformations, such as projections, are not one-to-one. The discussion emphasizes that the concept of closure applies to sets, not transformations themselves. Understanding these definitions clarifies the distinction between linear and nonlinear transformations.
yaganon
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right now, my concept for their difference is that linear transformations are 1 to 1, where as nonlinear transformations are not. However, P^n to P^(-1) is a linear transformation, but it's not 1 to 1.

the textbook def of linear transformation is that it must be closed under addition and scale factorization.

I'm confused.
 
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A linear transformation is just one that satisfies the conditions of linearity:

T(x+y)=T(x)+T(y)
T(ax)=aT(x)

where x and y are vectors, a a scalar. Nothing requires linear transformations to be 1 to 1 (they usually aren't) or nonlinear transformations to not be 1-1
 
yaganon said:
right now, my concept for their difference is that linear transformations are 1 to 1, where as nonlinear transformations are not. However, P^n to P^(-1) is a linear transformation, but it's not 1 to 1.

the textbook def of linear transformation is that it must be closed under addition and scale factorization.

I'm confused.
Yes, you are. It makes no sense to talk about a transformation as being "closed under addition and scale factorization". Only sets are "closed" under given operations, not transformations. A "linear transformation" on a vector space is a function, F(v), such that F(au+ bv)= aF(u)+ bF(v). They are certainly NOT, in general, "one-to-one", as Office Shredder says. For example, any projection is linear but is not one-to-one.
 
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