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  • Terminology

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  • Definition of augmented matrix (of a linear system)
  • Definition of coefficient matrix of a linear system
  • Definition of constant vector of a linear system
  • Definition of solution vector of a linear system
  • Definition of matrix representation of a linear system
  • Definition of domain of a linear transformation
  • Definition of codomain of a linear transformation
  • Definition of image (of a point) under a linear transformation
  • Definition of pre-image (of a point) under a linear transformation
  • Definition of onto/surjective linear transformation
  • Definition of one-to-one/injective linear transformation
  • Definition of range of linear transformation
  • Definition of kernel of linear transformation
  • Definition of invertible linear transformation
  • Definition of inverse of a linear transformation
  • Non-example of a linear transformation
  • Definition of linear transformation/homomorphism
  • Definition of identity linear transformation
  • Definition of sum of linear transformations
  • The sum of linear transformations is a linear transformation
  • Definition of scalar multiple of a linear transformation
  • A scalar multiple of a linear transformation is a linear transformation
  • Definition of pre-image of linear transformation
  • Definition of range of a linear transformation
  • Definition of invertible/nonsingular linear transformation
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Description:Added invertible/nonsingular definition
# Definition of invertible/nonsingular linear transformation

Put content here.**Definition:** A linear transformation \(T: V 	o W\) is *invertible* (or *nonsingular*) if there exists a linear transformation \(T^{-1}: W 	o V\) such that:
\[T^{-1} \circ T = I_V \quad 	ext{and} \quad T \circ T^{-1} = I_W\]
⏎
The term *nonsingular* is sometimes used, particularly when the transformation is represented by a matrix: a matrix is nonsingular if and only if its determinant is nonzero.
⏎
**Equivalent conditions** (for finite-dimensional spaces):
- \(T\) is invertible
- \(T\) is one-to-one and onto
- \(\ker(T) = \{\mathbf{0}\}\)
- \(	ext{range}(T) = W\)
- \(\dim(V) = \dim(W)\) and \(T\) is one-to-one
- The matrix of \(T\) is nonsingular (determinant is nonzero)

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* Terminology
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