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Runge–Kutta methods for linear ordinary differential equations
Applied Numerical Mathematics, 1999exaly
Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines
IEEE Transactions on Neural Networks and Learning Systems, 2012Siamak Mehrkanoon +2 more
exaly
The following problem is considered: \[ (1)\quad A(t)\dot x(t)=B(t)x(t)+F(t),\quad t_ 0\leq t\leq t_ 1;\quad(2)\quad x(t_ 0)=x_ 0. \] Here A(t), B(t) are \(n\times n\) matrices, rank \(\{A(t)\}=k=const\). for \(t\in [t_ 0,t,_ 1]\), F(t) is a known n- dimensional vector function, x(t) is the sought n-vector function and \(x_ 0\) is a given n-dimensional
openaire +2 more sources
openaire +2 more sources
Reduction of some systems of ordinary linear differential equations to a simpler form
Ukrainian Mathematical Journal, 1972openaire +3 more sources

