b) Implement an algorithm that solves the linear square simultaneous equation Ax b with QR decomposition and back substitution. Use the following code and the qr and backsub functions from a), as well as Numpy. Solve the simulataneous equation Ax b, with A numpy.array([1,2,-1,1-1,1,1]1,-4,1]]) and b numpy.array([1,2,3]) with your code Algorithm 11.2 SOLVING LINEAR EQUATIONS VIA QR FACTORIZATION given an n n invertible matrix and an n-vector b. 1. QR factorization. Compute the QR factorization A QR 2. Compute Qb 3. Back substitution. Sl the triangular equation Rr Q'b using back substi tution Begin with this code def linsolve(A,b): " Solves Ax-b"" # enter code here return x b) Implement an algorithm that solves the linear square simultaneous equation Ax b with QR decomposition and back substitution. Use the following code and the qr and backsub functions from a), as well as Numpy. Solve the simulataneous equation Ax b, with A numpy.array([1,2,-1,1-1,1,1]1,-4,1]]) and b numpy.array([1,2,3]) with your code Algorithm 11.2 SOLVING LINEAR EQUATIONS VIA QR FACTORIZATION given an n n invertible matrix and an n-vector b. 1. QR factorization. Compute the QR factorization A QR 2. Compute Qb 3. Back substitution. Sl the triangular equation Rr Q'b using back substi tution Begin with this code def linsolve(A,b): " Solves Ax-b"" # enter code here return x