(New page: A vector v is in the kernel of a matrix A if and only if Av=0. Thus, the kernel is the span of all these vectors. Similarly, a vector v is in the kernel of a [[linear transformati...)
 
 
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=What is a "kernel" in [[Linear_algebra|linear algebra]]?=
 
A vector v is in the kernel of a [[matrix]] A if and only if Av=0. Thus, the kernel is the [[span]] of all these vectors.
 
A vector v is in the kernel of a [[matrix]] A if and only if Av=0. Thus, the kernel is the [[span]] of all these vectors.
  
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0 \\
 
0 \\
 
0\end{bmatrix}
 
0\end{bmatrix}
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A related concept is that  of [[Image_(linear_algebra)|image of a matrix A]].
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The dimensions of the image and the kernel of A are related in the [[Rank_nullity_theorem_(linear_algebra)|Rank Nullity Theorem]]
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[[Linear_Algebra_Resource|Back to Linear Algebra Resource]]
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[[Category:MA351]]
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[[Category:linear algebra]]

Latest revision as of 05:31, 23 October 2013

What is a "kernel" in linear algebra?

A vector v is in the kernel of a matrix A if and only if Av=0. Thus, the kernel is the span of all these vectors.

Similarly, a vector v is in the kernel of a linear transformation T if and only if T(v)=0.

For example the kernel of this matrix (call it A)

$ \begin{bmatrix} 1 & 0 & 0\\ 0 & 2 & 1\end{bmatrix} $

is the following matrix, where s can be any number:

$ \begin{bmatrix} 0 \\ -s\\ 2s\end{bmatrix} $

Verification using matrix multiplaction: the first entry is $ 0*1-s*0+2s*0=0 $ and the second entry is $ 0*0-s*2+2s*1=0 $.

$ \begin{bmatrix} 1 & 0 & 0\\ 0 & 2 & 1\end{bmatrix}* \begin{bmatrix} 0 \\ -s\\ 2s\end{bmatrix}= \begin{bmatrix} 0 \\ 0\end{bmatrix} $

A related concept is that of image of a matrix A.

The dimensions of the image and the kernel of A are related in the Rank Nullity Theorem


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