Optimizing the coefficients of basis functions to fit a curve

\ Backslash or left matrix divide. A\B is the matrix division of A into B, which is roughly the same as INV(A)*B , except it is computed in a different way. If A is an N-by-N matrix and B is a column vector with N components, or a matrix with several such columns, then X = A\B is the solution to the equation A*X = B. A warning message is printed if A is badly scaled or nearly singular. A\EYE(SIZE(A)) produces the inverse of A. If A is an M-by-N rectangular matrix with M~=N and B is a column vector with M components, or a matrix with several such columns, then X = A\B is the solution in the least squares sense to the under- or overdetermined system of equations A*X = B. The effective rank, K, of A is determined from the QR decomposition with pivoting. A solution X is computed which has at most K nonzero components per column. If K < N this will usually not be the same solution as PINV(A)*B. A\EYE(SIZE(A)) produces a generalized inverse of A. X = MLDIVIDE(A,B) is called for the syntax 'A \ B' when A or B is an object. See MATLAB Operators and Special Characters for more details. See also LDIVIDE, RDIVIDE, MRDIVIDE, PAGEMLDIVIDE. Documentation for mldivide doc mldivide Other uses of mldivide codistributed/mldivide laurpoly/mldivide comm/mldivide StaticModel/mldivide distributed/mldivide sym/mldivide duration/mldivide symbolic/mldivide DynamicSystem/mldivide tall/mldivide gpuArray/mldivide timeseries/mldivide LagOp/mldivide tsdata.datametadata/mldivide