Fréchet derivative of the matrix exponential. function D = dexpm(X, H) Computes the directional derivative (the Fréchet derivative) of expm at X along H (square matrices). Thus, D = lim_(t -> 0) (expm(X + tH) - expm(X)) / t. Note: the adjoint of dexpm(X, .) is dexpm(X', .), which is a fact often useful to derive gradients of matrix functions involving expm(X). (This is wrt the inner product inner = @(A, B) real(trace(A'*B))). See also: dfunm dlogm dsqrtm

- dfunm Fréchet derivative of matrix functions.

0001 function D = dexpm(X, H) 0002 % Fréchet derivative of the matrix exponential. 0003 % 0004 % function D = dexpm(X, H) 0005 % 0006 % Computes the directional derivative (the Fréchet derivative) of expm at X 0007 % along H (square matrices). 0008 % 0009 % Thus, D = lim_(t -> 0) (expm(X + tH) - expm(X)) / t. 0010 % 0011 % Note: the adjoint of dexpm(X, .) is dexpm(X', .), which is a fact often 0012 % useful to derive gradients of matrix functions involving expm(X). 0013 % (This is wrt the inner product inner = @(A, B) real(trace(A'*B))). 0014 % 0015 % See also: dfunm dlogm dsqrtm 0016 0017 % This file is part of Manopt: www.manopt.org. 0018 % Original author: Nicolas Boumal, July 3, 2015. 0019 % Contributors: 0020 % Change log: 0021 0022 D = dfunm(@expm, X, H); 0023 0024 end

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