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A matrix derivation
In general, we agreed to x = (x1, x2, ... xN) Tx = (x1, x2, ... xN) T, which is the denominator layout. Common matrix derivation methods are: derivative vector to vector, scalar vector derivation, the scalar vector derivation.
1, the vector of the vector derivative
Numerator layout: molecular structure
Denominator layout: layout denominator
"Multivariate statistical analysis" class, in accordance with the terms of molecular structure.
2, a vector scalar derivative
3, the scalar vector derivation
Others can refer to wiki: Wikipedia matrix derivation formula
Second, several important matrix
1, the gradient (Gradient)
2, Jacobian matrix (Jacobian matrix)
3, Hessian matrix (Hessian matrix)
Third, the usual derivation of the matrix equation
Reference:
https://blog.csdn.net/xtydtc/article/details/51133903
https://blog.csdn.net/yc461515457/article/details/49682473
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Disclaimer: this article is the original article CSDN bloggers' end of Lemna minor lx ", and follow CC 4.0 BY-SA copyright agreement, reproduced, please attach the original source link and this statement.
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