#N canvas 335 0 568 576 10; #X obj 0 0 doc_h cv/; #X obj 0 547 doc_f; #X obj 19 160 cv/#SVD; #X text 200 46 Singular Value Decomposition; #X obj 3 306 doc_c 0; #X obj 3 346 doc_i 1; #X obj 3 408 doc_o 3; #X obj 14 376 doc_ii 0; #X obj 14 438 doc_oo 0; #X obj 14 460 doc_oo 1; #X obj 14 482 doc_oo 2; #X obj 97 438 doc_m o0 grid; #X obj 97 460 doc_m o1 grid; #X obj 97 482 doc_m o2 grid; #X obj 28 88 display; #X text 82 65 just turn into a real grid; #X obj 210 161 display; #X obj 210 225 display; #X obj 20 225 display; #X msg 19 46 3 3 f # 1 0 0 0 2 3 0 3 -2; #X obj 19 65 # + (f #); #X text 287 89 for finding eigenvalues and eigenvectors.; #X obj 97 376 doc_m i0 grid; #X text 200 376 N by N matrix to decompose; #X text 200 438 N by N diagonal matrix containing eigenvalues; #X text 200 460 N by N matrix containing eigenvectors; #X text 200 482 N by N matrix containing fudge factors: typically contains only zeroes \, ones \, and minus ones.; #X obj 3 527 doc_also; #X obj 97 527 #extract_diagonal; #X obj 211 527 cv/#Invert; #X connect 2 0 18 0; #X connect 2 1 17 0; #X connect 2 2 16 0; #X connect 11 1 24 0; #X connect 12 1 25 0; #X connect 13 1 26 0; #X connect 19 0 20 0; #X connect 20 0 14 0; #X connect 20 0 2 0; #X connect 22 1 23 0; #X connect 27 1 28 0; #X connect 27 1 29 0;