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-rwxr-xr-x[-rw-r--r--]numlib/svd.h35
1 files changed, 33 insertions, 2 deletions
diff --git a/numlib/svd.h b/numlib/svd.h
index 59b080d..6a89210 100644..100755
--- a/numlib/svd.h
+++ b/numlib/svd.h
@@ -13,13 +13,44 @@
extern "C" {
#endif
+/*
+
+ U[] decomposes A[]'s columns into orthogonal, singular vectors.
+ U[]'s columns are vectors that sum to 1.0, i.e. they leave a vectors normal unchanged.
+ The inverse of U[] is its transpose.
+ U[]'s columns corresponding to non-zero W[] are the orthonormal vectors that span
+ the (input) RANGE space. Columns corresponding to zero W[] are zero.
+
+ W[] will return singlular values, i.e. the weighting of the singular vectors.
+ It's inverse is is the reciprical of its elements.
+
+ V[] composes the singular vectors back into A[]'s rows.
+ V[]'s columns and rows are orthonormal.
+ V[]'s columns corresponding to non-zero W[] are the orthonormal vectors that span
+ the (output) RANGE space.
+ v[]'s columns corresponding to zero W[] are the (output) othonormal vectors that span
+ the NULL space.
+ The inverse of V[] is its transpose.
+
+ To re-form, A = U.W.Vt, i.e. multiply by transpose of V.
+
+ i.e. mult. input vector[m] by U[] converts to [n] compact, orthogonal
+ basis vectors. W then scales them appropiately, setting null space
+ vectors to 0. V[] then transforms from the orthogonal basis vectors
+ to A[]'s output space.
+
+ To reveal NULL space, make sure n >= m, since U[] vectors corrsponding
+ to zero's are set to zero.
+
+*/
+
/* Compute Singular Value Decomposition of A = U.W.Vt */
/* Return status value: */
/* 0 - no error */
/* 1 - m < n error */
int svdecomp(
-double **a, /* A[0..m-1][0..n-1], return U[][] */
-double *w, /* return W[0..n-1] */
+double **a, /* A[0..m-1][0..n-1], return U[0..m-1][0..n-1] */
+double *w, /* return W[0..n-1] = singular values */
double **v, /* return V[0..n-1][0..n-1] (not transpose!) */
int m, /* Number of equations */
int n /* Number of unknowns */