def backtracking1(A,b,x,n):
    nu=1
    for t in range(0,n):
        nu=2*nu
        condition = False
        while condition==False:
            before = x
            x = x-nu*gradient(A,b,x)
            if np.linalg.norm(x,1)<=1 and funcion(A,b,x) <= funcion(A,b,before)+np.dot(gradient(A,b,before).T,x-before)+(1/nu)*(np.linalg.norm(x-before)**2):
                condition = True
            else:
                nu = nu/2
                x = before
    return x