This work is devoted to finding maxima of the function where and is a large sparse matrix whose eigenvalues have negative real parts but whose numerical range ...
Such maxima will be referred to as humps for the matrix exponential. The humps are needed, for example, for determining the transient growth in fluid mechanics, ...
Oct 22, 2024 · The fundamental idea of the proposed method is to compute only the action of the matrix exponential on a given state vector instead of computing ...
This work is devoted to finding maxima of the function (t)=exp(tA)2 where t0 and A is a large sparse matrix whose eigenvalues have negative real parts but ...
The matrix exponential eAt forms the basis for the homogeneous (unforced) and the forced response of LTI systems. We consider here a method of determining ...
Methods involv- ing approximation theory, differential equations, the matrix eigenvalues, and the matrix characteristic polynomial have been proposed.
The scaling and squaring method is the most widely used method for computing the matrix exponential, not least because it is the method implemented in the ...
Sep 12, 2022 · In this video we show how to compute the matrix exponential using the modal method (AKA diagonalization). This involves computing the ...
eP = I + (e − 1)P. Deriving this by expansion of the exponential function, each power of P reduces to P which becomes a common factor of the sum:
Jan 17, 2020 · My suggestion is to use scipy.linalg.expm. It's really easy to use basically you have the X matrix and you just pass it to the scipy.linalg.expm class.