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In mathematics, in the field of control theory, a Sylvester equation is a matrix equation of the form: [1] + =. It is named after English mathematician James Joseph Sylvester. Then given matrices A, B, and C, the problem is to find the possible matrices X that obey this equation.
The matrix equation AX=XB, where X is unknown, has an infinite number of solutions that can be easily studied by a geometrical approach. [8] To find X it is necessary to consider a simultaneous set of 2 equations A 1 X=XB 1 and A 2 X=XB 2; the matrices A 1, A 2, B 1, B 2 have to be dermined by experiments to be performed in an optimized way. [9]
In numerical linear algebra, the Bartels–Stewart algorithm is used to numerically solve the Sylvester matrix equation =.Developed by R.H. Bartels and G.W. Stewart in 1971, [1] it was the first numerically stable method that could be systematically applied to solve such equations.
When both A and B are n × n matrices, the trace of the (ring-theoretic) commutator of A and B vanishes: tr([A, B]) = 0, because tr(AB) = tr(BA) and tr is linear. One can state this as "the trace is a map of Lie algebras gl n → k from operators to scalars", as the commutator of scalars is trivial (it is an Abelian Lie algebra ).
The conjugate gradient method can be applied to an arbitrary n-by-m matrix by applying it to normal equations A T A and right-hand side vector A T b, since A T A is a symmetric positive-semidefinite matrix for any A. The result is conjugate gradient on the normal equations (CGN or CGNR). A T Ax = A T b
Input: initial guess x (0) to the solution, (diagonal dominant) matrix A, right-hand side vector b, convergence criterion Output: solution when convergence is reached Comments: pseudocode based on the element-based formula above k = 0 while convergence not reached do for i := 1 step until n do σ = 0 for j := 1 step until n do if j ≠ i then ...
For example, if A is a 3-by-0 matrix and B is a 0-by-3 matrix, then AB is the 3-by-3 zero matrix corresponding to the null map from a 3-dimensional space V to itself, while BA is a 0-by-0 matrix. There is no common notation for empty matrices, but most computer algebra systems allow creating and computing with them.
In mathematics, matrix calculus is a specialized notation for doing multivariable calculus, especially over spaces of matrices.It 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.