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#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;
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