digest_matrix calculus

Matrix Calculus

Jie FuSaturday, April 8, 2023

https://sites.google.com/site/bigaidream/

Matrix calculus collects the various partial derivatives of a single function with respect to many variables, and/or of a multivariate function with respect to a single variable, into vectors and matrices that can be treated as single entities. Reference: http://en.wikipedia.org/wiki/Matrix_calculus

ContentsMatrix Calculus...............................................................................................................................................................1Scope.............................................................................................................................................................................. 1Notation..........................................................................................................................................................................2Derivatives with Vectors.................................................................................................................................................2

Vector-by-scalar......................................................................................................................................................2Scalar-by-vector......................................................................................................................................................3Vector-by-vector.....................................................................................................................................................3

Derivatives with Matrices...............................................................................................................................................3Matrix-by-scalar......................................................................................................................................................3Scalar-by-matrix......................................................................................................................................................4

Identities.........................................................................................................................................................................5Vector-by-vector identities......................................................................................................................................5Scalar-by-vector identities.......................................................................................................................................6Vector-by-scalar identities......................................................................................................................................8Scalar-by-matrix identities......................................................................................................................................9Matrix-by-scalar identities....................................................................................................................................10Scalar-by-scalar identities.....................................................................................................................................11

With vectors involved...................................................................................................................................11With matrices involved.................................................................................................................................11

Identities in differential form................................................................................................................................11

Scope

For a scalar function of three independent variables, , the gradient is given by the vector equation

,

where represents a unit vector in the direction for . This type of generalized derivative can be seen as the derivative of a scalar, f, with respect to a vector, and its result can be easily collected in vector form.

Notation

All functions are assumed to be of differentiability class C1 unless otherwise noted. Generally letters from first half of the alphabet (a, b, c, …) will be used to denote constants, and from the second half (t, x, y, …) to denote variables.

Derivatives with Vectors

Vector-by-scalar

The derivative of a vector , by a scalar x is written (in numerator layout notation) as

Scalar-by-vector

The derivative of a scalar y by a vector , is written (in numerator layout notation) as

Vector-by-vector

The derivative of a vector function (a vector whose components are functions) , of an independent

vector , is written (in numerator layout notation) as

Derivatives with Matrices

Matrix-by-scalar

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

Scalar-by-matrix

The derivative of a scalar y function of a matrix X of independent variables, with respect to the matrix X, is given (in numerator layout notation) by

Identities

Vector-by-vector identities

Scalar-by-vector identities

Vector-by-scalar identities

Scalar-by-matrix identities

Matrix-by-scalar identities

Scalar-by-scalar identities

With vectors involved

With matrices involved

Identities in differential form

It is often easier to work in differential form and then convert back to normal derivatives. This only works well using

the numerator layout.

To convert to normal derivative form, first convert it to one of the following canonical forms, and then use these identities: