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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 kernel content
# Definition of kernel of linear transformation

Put content here.**Definition:** The *kernel* (or *null space*) of a linear transformation \(T: V \to W\) is the set of all vectors in the domain that map to the zero vector:
\[\ker(T) = \{\mathbf{v} \in V : T(\mathbf{v}) = \mathbf{0}\}\]
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The kernel is always a subspace of the domain \(V\).
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**Example:** For \(T: \mathbb{R}^3 \to \mathbb{R}^2\) defined by \(T(x,y,z) = (x,y)\), the kernel is \(\{(0,0,z) : z \in \mathbb{R}\}\) (the z-axis).
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**Example:** For \(T: \mathbb{R}^2 \to \mathbb{R}^2\) defined by \(T(x,y) = (x+y, x+y)\), the kernel is \(\{(x,-x) : x \in \mathbb{R}\}\) (the line \(y = -x\)).
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**Key facts:**
- \(T\) is one-to-one iff \(\ker(T) = \{\mathbf{0}\}\)
- \(\dim(\ker T)\) is called the *nullity* of \(T\)
- The kernel measures how far \(T\) is from being injective

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* Terminology
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