maths.free › Linear Algebra › Matrix inverse
Matrix inverse
The 2×2 formula and Gauss-Jordan elimination for the rest.
A⁻¹ is the matrix that undoes A. For 2×2 there is a formula; for anything bigger, row-reduce [A | I] until A becomes I, and the identity becomes A⁻¹. Every row operation is shown.
Ejemplo resuelto · inverse of [[1,2],[3,4]]
Inverse of [[1,2],[3,4]]
Paso a paso
- \det A = -2
A matrix is invertible only when its determinant is non-zero.
- A^{-1} = \frac{1}{\det A}\begin{pmatrix} d & -b \\ -c & a \end{pmatrix} = \frac{1}{-2}\left[\begin{matrix}4 & -2\\-3 & 1\end{matrix}\right]
For 2×2: swap the diagonal, negate the off-diagonal, divide by the determinant.
- A^{-1} = \left[\begin{matrix}-2 & 1\\\frac{3}{2} & - \frac{1}{2}\end{matrix}\right]
Revelar la respuesta
Ahora tú Escoge un problema, o escribe o dibuja el tuyo. Cada paso, una imagen, la respuesta oculta hasta que preguntes.
Una cuenta gratuita añade notas sobre cada lección, un registro de lo que has terminado, tus problemas resueltos en un lugar, y un tutor que puedes preguntar sobre esta página. Las matemáticas en sí están abiertas a todos, se han registrado o no.
Registrarse Inicio de sesiónSímbolos utilizados aquí
Toque cualquier símbolo para la definición completa, una imagen, y lo que cada letra en ella significa.
Cómo: Matrix inverse
- A matrix is invertible only when its determinant is non-zero.
- For 2×2: swap the diagonal, negate the off-diagonal, divide by the determinant.
Preguntas que la gente hace
What does a determinant mean geometrically?
It is the factor by which the matrix scales area (2×2) or volume (3×3), with a negative sign if orientation flips. Zero means the matrix flattens space and cannot be undone.
What is an eigenvector?
A direction the matrix does not turn: it only stretches it by the eigenvalue. Along eigenvectors a complicated matrix acts like multiplication by a number.
Why is matrix multiplication not commutative?
Because a matrix is a transformation and AB means "do B, then A". Rotating then reflecting is not the same as reflecting then rotating.
Más en Linear Algebra
DeterminantsEigenvalues and eigenvectorsMatrix multiplicationRow reductionVector spaces, span and linear independenceOrthogonality, projections and least squaresDiagonalisation and matrix powersLinear transformations and change of basis