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HPLC-DAD. w. 2. w. S. HPLC-DAD data. 2. C. t. t. =. Suppose in a chromatogram obtained with a HPLC-DAD there is a peak which an impurity is co-eluted with analyte and you know analyte. Apply orthogonal projection concept and obtain the chromatographic profile of impurity.
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w 2 w S HPLC-DAD data 2 C t t = Suppose in a chromatogram obtained with a HPLC-DAD there is a peak which an impurity is co-eluted with analyte and you know analyte. Apply orthogonal projection concept and obtain the chromatographic profile of impurity.
? Apply the HPLC-DAD m.file on noised data and check the accuracy of the method
… p … n Matrices From a geometrical point of view, we can interpret a matrix with n rows and p columns either as a pattern of n points in a p-dimensional space, or as a pattern of p points in n-dimensional space
1 2 3 4 5 6 Two vectors in a three dimensional space Three vectors in a two dimensional space
xj p xiT n up vn xi xj u1 v1 uj vi Geometrical interpretation of an n x p matrix X xij Pn Sp Sn Pp xij xij
p X n rank(Pp) = rank(Pn) = rank(X) < min (n, p) Rank The rank of matrix X is equal to the number of linearly independent vectors from which all p columns of X can be constructed as their linear combination Geometrically, the rank of pattern of p point can be seen as the minimum number of dimension that is required to represent the p point in the pattern together with origin of space
l1 l2 l3 Conc. e l1 l2 l3 s1 0.1 0.2 0.3 0.2 0.4 0.6 l2= 2l1 s2 l3= 3l1 Rank of the real chemical matrix 1 2 0.1 0.2 0.3 s2= 2s1 rank of a ideal chemical matrix number of chemical species =
Anal.m file Constructing the data matrix for further analysis