Find minimum-norm-residual solution to AX=B
Math Functions / Matrices and Linear Algebra / Linear System Solvers
The QR Solver block solves the linear system AX=B, which can be
overdetermined, underdetermined, or exactly determined. The system is solved by applying
QR factorization to the M-by-N matrix, A, at the
A port. The input to
B port is the right side M-by-L matrix, B. The block treats
length-M unoriented vector input as an M-by-1 matrix.
The output at the
x port is the N-by-L matrix, X. X is chosen to
minimize the sum of the squares of the elements of B-AX. When B is
a vector, this solution minimizes the vector 2-norm of the residual (B-AX is the
residual). When B is a matrix, this solution minimizes the matrix Frobenius norm of the
residual. In this case, the columns of X are the solutions to the L corresponding
systems AXk=Bk, where
Bk is the kth column of B, and Xk is
the kth column of X.
X is known as the minimum-norm-residual solution to AX=B. The minimum-norm-residual solution is unique for overdetermined and exactly determined linear systems, but it is not unique for underdetermined linear systems. Thus when the QR Solver is applied to an underdetermined system, the output X is chosen such that the number of nonzero entries in X is minimized.
Simulate using— Type of simulation to run
Interpreted execution(default) |
Simulate model using the MATLAB® interpreter. This option shortens startup time and
has faster simulation speed compared to
Simulate model using generated C code. The first time you run a simulation, Simulink® generates C code for the block. The C code is reused for subsequent simulations, as long as the model does not change. This option requires additional startup time but provides faster subsequent simulations.
QR factorization factors a column-permuted variant (Ae) of the M-by-N input matrix A as
Ae = QR
where Q is a M-by-min(M,N) unitary matrix, and R is a min(M,N)-by-N upper-triangular matrix.
The factored matrix is substituted for Ae in
AeX = Be
QRX = Be
is solved for X by noting that Q-1 = Q* and substituting Y = Q*Be. This requires computing a matrix multiplication for Y and solving a triangular system for X.
RX = Y
Double-precision floating point
Single-precision floating point
Generated code relies on
memset functions (
string.h) under certain