This results in an error message: "General::luc: Result for 1 of badly conditioned matrix 2 may contain significant numerical errors." and trimendous errors. Namely, we can use matrix algebra to multiply both sides of the equation by A 1, thus. 1 2 4 5x y 1 13 1 2 4 5 x y 1 13 Find the inverse of the coefficient matrix.
Find the AX B A X B from the system of equations. If you have a nearly linear dependent basis for your equations, it may help, first to search for a new orthogonalized basis, write the equation in this basis and then solve the equations.Īs an example we solve a 3D problem: Given a not orthogonal badly conditioned basis: bas and a vector v, we are searching coefficients: coef, so that coef.bas = v: b1 = *) equating the elements of each matrix, thus getting our linear system back again: Given a system of linear equations in two unknowns 2x+ 4y 2 3x+ 7y 7 We can solve this system of equations using the matrix identity AX B if the matrix A has an inverse. x + 2y 1 x + 2 y 1, 4x + 5y 13 4 x + 5 y 13.
Are this equations linear ? If so you can try to transform the equations.