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Home > Matrix & Vector calculators > Null Space example (Nullity of a matrix)
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24. Null Space example
( Enter your problem )
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- Example `[[1,-2,0,3,-4],[3,2,8,1,4],[2,3,7,2,3],[-1,2,0,4,-3]]`
- Example `[[1,2,3,2],[3,0,1,8],[2,-2,-2,6]]`
- Example `[[3,-1,-1],[2,-2,1]]`
- Example `[[-2,2,6,0],[0,6,7,5],[1,5,4,5]]`
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Other related methods
- Transforming matrix to Row Echelon Form
- Transforming matrix to Reduced Row Echelon Form
- Rank of matrix
- Characteristic polynomial of matrix
- Eigenvalues
- Eigenvectors (Eigenspace)
- Triangular Matrix
- LU decomposition using Gauss Elimination method of matrix
- LU decomposition using Doolittle's method of matrix
- LU decomposition using Crout's method of matrix
- Diagonal Matrix
- Cholesky Decomposition
- QR Decomposition (Gram Schmidt Method)
- QR Decomposition (Householder Method)
- LQ Decomposition
- Pivots
- Singular Value Decomposition (SVD)
- Moore-Penrose Pseudoinverse
- Power Method for dominant eigenvalue
- determinants using Sarrus Rule
- determinants using properties of determinants
- Row Space
- Column Space
- Null Space
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1. Example `[[1,-2,0,3,-4],[3,2,8,1,4],[2,3,7,2,3],[-1,2,0,4,-3]]` (Previous example) | 3. Example `[[3,-1,-1],[2,-2,1]]` (Next example) |
2. Example `[[1,2,3,2],[3,0,1,8],[2,-2,-2,6]]`
Find Null Space ... `[[1,2,3,2],[3,0,1,8],[2,-2,-2,6]]`
Solution:
| `1` | `2` | `3` | `2` | | | `3` | `0` | `1` | `8` | | | `2` | `-2` | `-2` | `6` | |
Now, reduce the matrix to reduced row echelon form `R_2 larr R_2-3xx R_1`
= | | `1` | `2` | `3` | `2` | | | `0` | `-6` | `-8` | `2` | | | `2` | `-2` | `-2` | `6` | |
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`R_3 larr R_3-2xx R_1`
= | | `1` | `2` | `3` | `2` | | | `0` | `-6` | `-8` | `2` | | | `0` | `-6` | `-8` | `2` | |
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`R_2 larr R_2-:-6`
= | | `1` | `2` | `3` | `2` | | | `0` | `1` | `4/3` | `-1/3` | | | `0` | `-6` | `-8` | `2` | |
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`R_1 larr R_1-2xx R_2`
= | | `1` | `0` | `1/3` | `8/3` | | | `0` | `1` | `4/3` | `-1/3` | | | `0` | `-6` | `-8` | `2` | |
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`R_3 larr R_3+6xx R_2`
= | | `1` | `0` | `1/3` | `8/3` | | | `0` | `1` | `4/3` | `-1/3` | | | `0` | `0` | `0` | `0` | |
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The rank of a matrix is the number of non all-zeros rows `:. Rank = 2`
Null Space : Now, solve the matrix equation
| `1` | `0` | `1/3` | `8/3` | | | `0` | `1` | `4/3` | `-1/3` | | | `0` | `0` | `0` | `0` | |
| | | = | |
`x_1+1/3x_3+8/3x_4=0`
`x_2+4/3x_3-1/3x_4=0`
Add equation for each free variable `x_1+1/3x_3+8/3x_4=0`
`x_2+4/3x_3-1/3x_4=0`
`x_3=x_3`
`x_4=x_4`
Solve for each variable in terms of the free variables `x_1=-1/3x_3-8/3x_4`
`x_2=-4/3x_3+1/3x_4`
`x_3=x_3`
`x_4=x_4`
Convert this into vectors
| = | | `-1/3x_3-8/3x_4` | | | `-4/3x_3+1/3x_4` | | | `x_3` | | | `x_4` | |
| = | `[[-1/3],[-4/3],[1],[0]]` | `x_3` | `+` | `[[-8/3],[1/3],[0],[1]]` | `x_4` |
Thus, the basis for the null space is `[[-1/3],[-4/3],[1],[0]],[[-8/3],[1/3],[0],[1]]`
This material is intended as a summary. Use your textbook for detail explanation. Any bug, improvement, feedback then
1. Example `[[1,-2,0,3,-4],[3,2,8,1,4],[2,3,7,2,3],[-1,2,0,4,-3]]` (Previous example) | 3. Example `[[3,-1,-1],[2,-2,1]]` (Next example) |
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