function EPT_ConvexOP_MinSearch(A,c,b_0,b_star,lambda,mu)
tic
% Convex Optimisation for an EPT function with dominant real pole identified
% as mu e^{lambda x} and the pair (A,c) also provided. An initial guess is
% required as the "b_guess" estimate.
% Plots original EPT function and final approximation. Accuracy may be
% improved by reducing the tolerance in FindingAlpha
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Example
% mu = 16;
% lambda = -0.5;
% c = [-30 15];
% A = [-1 0;0 -2];
% b_star = [1;1];
% b_0 = [0.950;2.175];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
T = Finite_T(A,b_star,c,mu,lambda);
A = A - lambda*eye(2);
Q = lyap(A,c'*c);
OPTS = OPTIMSET('fminsearch');
OPTIONS = OPTIMSET(OPTS, 'TolX', 1e-10, 'TolFun', 1e-10, 'Display', 'off', 'MaxFunEvals',100);
b_hat = fminsearch('Convex_Optimisation', b_0', OPTIONS, Q, A, c, b_star, mu, lambda, T)';
BB_Star = FindingAlpha(A,c,b_star,b_hat,mu,lambda,T);
bd = (BB_Star-b_star);
Q_Norm = sqrt(bd'*Q*bd)
Plot_EPT_DP(A,BB_Star,b_star,c,mu,lambda,T)
toc
end