GNS

description:

[X,err]=GNS(V,M,vars,tol,rank_bound) prepares a matrix X for the AWbd function by performing the Gelfand-Naimark-Segal construction.

arguments:

V - cell of all monomials of degree up to d

M - a flat square matrix

vars - cell of variables

tol - tolerance for computing the rank of a matrix

rank_bound - optional upper bound for the rank of a matrix

output:

X - a matrix where each of its rows represents a square matrix

err - if it equals 0 means that program ended with success otherwise the procedure failed

possible usage:

GNS(V,M,vars), GNS(V,M,vars,tol), GNS(V,M,vars,tol,rank_bound)