Shortest path using Artificial Neural Networks
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I am working on my Master Thesis
My equations are of form Ax=b
Inputs: For every A (mxn matrix) there are different b vectors
Outputs: For every b we have x vector and a scalar
Example
Input....................: Outputs
A(mxn); b1 (mx1): x1[vector], +a1
A(mxn); b2 (mx1): x2[vector], +a2
A(mxn); b3 (mx1): x3[vector], +a3
.................................
.................................
.................................
B(lxk); c1 (lx1): y1[vector], +d1
B(lxk); c2 (lx1): y2[vector], +d2
B(lxk); c3 (lx1): y3[vector], +d3
.................................
.................................
I want to train these set with neural networks and see if i am getting valid output vector and scalar for every other given Matrix H (*x*) and vector e(*x1) belongs to the same kind of problem.
Any Help would be appreciated. Thank you!
Best Regards, Veeranki
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