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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 definition of coefficient matrix
# Definition of coefficient matrix of a linear system

Put content here**Definition: Coefficient Matrix**
⏎
The coefficient matrix of a linear system is the `m × n` matrix containing only the coefficients of the variables, without the constant terms.
⏎
For the system:
```
a₁₁x₁ + a₁₂x₂ + ... + a₁ₙxₙ = b₁
a₂₁x₁ + a₂₂x₂ + ... + a₂ₙxₙ = b₂
...
aₘ₁x₁ + aₘ₂x₂ + ... + aₘₙxₙ = bₘ
```
⏎
The coefficient matrix `A` is:
```
A = [a₁₁ a₁₂ ... a₁ₙ]
    [a₂₁ a₂₂ ... a₂ₙ]
    [...  ...  ... ...]
    [aₘ₁ aₘ₂ ... aₘₙ]
```
⏎
Each row corresponds to one equation, and each column corresponds to one variable. The coefficient matrix is denoted `A` in the standard form `Ax = b`.

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