Orodruin said:
Orodruin said:
Orodruin said:
Orodruin said:
Matrix-by-scalarEdit
The derivative of a matrix function
Y by a scalar
x is known as the
tangent matrix and is given (in
numerator layout notation) by
{\displaystyle {\frac {\partial \mathbf {Y} }{\partial x}}={\begin{bmatrix}{\frac {\partial y_{11}}{\partial x}}&{\frac {\partial y_{12}}{\partial x}}&\cdots &{\frac {\partial y_{1n}}{\partial x}}\\{\frac {\partial y_{21}}{\partial x}}&{\frac {\partial y_{22}}{\partial x}}&\cdots &{\frac {\partial y_{2n}}{\partial x}}\\\vdots &\vdots &\ddots &\vdots \\{\frac {\partial y_{m1}}{\partial x}}&{\frac {\partial y_{m2}}{\partial x}}&\cdots &{\frac {\partial y_{mn}}{\partial x}}\\\end{bmatrix}}.}
Scalar-by-matrixEdit
The derivative of a scalar
y function of a
p×
q matrix
X of independent variables, with respect to the matrix
X, is given (in
numerator layout notation) by
{\displaystyle {\frac {\partial y}{\partial \mathbf {X} }}={\begin{bmatrix}{\frac {\partial y}{\partial x_{11}}}&{\frac {\partial y}{\partial x_{21}}}&\cdots &{\frac {\partial y}{\partial x_{p1}}}\\{\frac {\partial y}{\partial x_{12}}}&{\frac {\partial y}{\partial x_{22}}}&\cdots &{\frac {\partial y}{\partial x_{p2}}}\\\vdots &\vdots &\ddots &\vdots \\{\frac {\partial y}{\partial x_{1q}}}&{\frac {\partial y}{\partial x_{2q}}}&\cdots &{\frac {\partial y}{\partial x_{pq}}}\\\end{bmatrix}}.}
Important examples of scalar functions of matrices include the
trace of a matrix and the
determinant.
In analog with
vector calculus this derivative is often written as the following.
{\displaystyle \nabla _{\mathbf {X} }y(\mathbf {X} )={\frac {\partial y(\mathbf {X} )}{\partial \mathbf {X} }}}
Also in analog with
vector calculus, the
directional derivative of a scalar
f(
X) of a matrix
X in the direction of matrix
Y is given by
{\displaystyle \nabla _{\mathbf {Y} }f=\operatorname {tr} \left({\frac {\partial f}{\partial \mathbf {X} }}\mathbf {Y} \right).}
It is the gradient matrix, in particular, that finds many uses in minimization problems in
estimation theory, particularly in the
derivation of the
Kalman filter algorithm, which is of great importance in the field.