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How to solve Ax=B complex matrix system in F 77

How to solve Ax=B complex matrix system in F 77

How to solve Ax=B complex matrix system in F 77

(OP)
Hi all

 i want to solve a complex linear algebra equation in the form of
 Ax = B.  ( A, B are known and need to find B)
 where A and B are complex.. A(n,n) & B (n,1) & x (n,1)

 i want this to be solved using Fortran 77.

 I've used Linpack solvers to solve Ax=B , when A,B,x all are real     values
   call solver (A,B,NETOT,1,z)
   solver contains Linpack subroutines
but the same code does not work when A,B are complex matrices
   
     

RE: How to solve Ax=B complex matrix system in F 77

Do you have a list of all the functions you have access to? There must be a couple of functions for solving a set of this type, one function for real and the same function with a 'c' (for complex) as a first letter for a complex values system.

This page http://www.netlib.org/linpack/  has some functions listed there...

 

RE: How to solve Ax=B complex matrix system in F 77

Are you expecting x to be complex or real?

If x is real, then all you need to fill in is the real part of the complex number into A and B and check it with the imaginary part of A and B.  If the imaginary part doesn't match then there is no solution.  It is a different problem if x is complex.

RE: How to solve Ax=B complex matrix system in F 77

(OP)
Thanks a lot xwb and salgerman for your kind attention

 in my problem of Ax = B , all i know is i ve got A and B matrices like given from previous calculations.

 in A matrix some values are having only real parts and others are having both real and imaginary parts.

 in B matrix all the values are imaginary values (it is a column matrix actually)

 x matrix is THE one i need as solution , and it is unknown.

 

RE: How to solve Ax=B complex matrix system in F 77

Hi asela23

there are different ways to solve the linear system Ax = b. From your first post you I see that x and b are vectors and A is symmetric. You get x by inverting the coefficient matrix A -> x = A^-1 b.
Inversion of A can be done by an iterative method like preconditioned conjugated gradients, quasi minimal residual or directly by a LU decomposition. If you have the intel compiler you can use the mkl library that comes with the compiler, there are linear system solvers included.

 

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