new examples for ann_mlp

svn path=/trunk/externals/ann/; revision=3012
author: Davide Morelli <morellid@users.sourceforge.net> 2005-05-18 15:55:28 +0000
committer: Davide Morelli <morellid@users.sourceforge.net> 2005-05-18 15:55:28 +0000
commit: f64944ede13a3f95e9ad3130c74a53833f1a04bf (patch)
tree: 398a9486fc77bc1a7308f94fd048f56963c6e48e
parent: 4c962acc9f2b6e275f02ab7660a8471453c2f393 (diff)
12 files changed, 2272 insertions, 0 deletions
diff --git a/examples/ann_mlp_example1/train-and.txt b/examples/ann_mlp_example1/train-and.txt
new file mode 100755
index 0000000..4534273
--- /dev/null
+++ b/examples/ann_mlp_example1/train-and.txt
@@ -0,0 +1,9 @@
+4 2 1
+0 0
+0
+1 0
+0
+0 1
+0
+1 1
+1
diff --git a/examples/ann_mlp_example1/train-or.txt b/examples/ann_mlp_example1/train-or.txt
new file mode 100755
index 0000000..733750a
--- /dev/null
+++ b/examples/ann_mlp_example1/train-or.txt
@@ -0,0 +1,9 @@
+4 2 1
+0 0
+0
+1 0
+1
+0 1
+1
+1 1
+1
diff --git a/examples/ann_mlp_example1/train-xor.txt b/examples/ann_mlp_example1/train-xor.txt
new file mode 100755
index 0000000..fec3e31
--- /dev/null
+++ b/examples/ann_mlp_example1/train-xor.txt
@@ -0,0 +1,9 @@
+4 2 1
+0 0
+0
+1 0
+1
+0 1
+1
+1 1
+0
diff --git a/examples/ann_mlp_example1/xor.pd b/examples/ann_mlp_example1/xor.pd
new file mode 100755
index 0000000..b2c9fe1
--- /dev/null
+++ b/examples/ann_mlp_example1/xor.pd
@@ -0,0 +1,89 @@
+#N canvas 438 239 531 379 10;
+#X msg 50 22 create 2 1;
+#X msg 69 64 train-on-file train-xor.txt;
+#X obj 22 306 nbx 5 14 -1e+037 1e+037 0 0 empty empty output 0 -6 0
+10 -262144 -1 -1 0 256;
+#X msg 117 225 0 0;
+#X msg 152 226 0 1;
+#X msg 191 227 1 0;
+#X msg 228 227 1 1;
+#X text 118 262 once saved you can load your nn at load time using
+passing the filename as argument;
+#X msg 111 167 save xor.net;
+#N canvas 180 57 553 390 train 0;
+#X obj 43 283 outlet;
+#X msg 46 17 train;
+#X obj 168 137 tgl 15 0 empty empty in1 0 -6 0 8 -262144 -1 -1 0 1
+;
+#X obj 205 137 tgl 15 0 empty empty in2 0 -6 0 8 -262144 -1 -1 0 1
+;
+#X obj 246 138 tgl 15 0 empty empty out 0 -6 0 8 -262144 -1 -1 0 1
+;
+#X obj 113 137 bng 15 250 50 0 empty empty train! 0 -6 0 8 -262144
+-1 -1;
+#X obj 115 160 pack s f f f;
+#X obj 114 181 unpack s f f f;
+#X obj 136 202 pack f f f;
+#X msg 153 265 run;
+#N canvas 0 0 534 398 auto 0;
+#X obj 210 333 outlet;
+#X text 68 37 auto train OR;
+#X obj 193 35 tgl 15 0 empty empty empty 0 -6 0 8 -262144 -1 -1 0 1
+;
+#X obj 194 63 metro 10;
+#X msg 126 194 0 0 0;
+#X msg 169 194 1 0 1;
+#X msg 212 196 0 1 1;
+#X msg 255 196 1 1 1;
+#X obj 191 124 select 0 1 2 3;
+#X obj 193 96 random 4;
+#X connect 2 0 3 0;
+#X connect 3 0 9 0;
+#X connect 4 0 0 0;
+#X connect 5 0 0 0;
+#X connect 6 0 0 0;
+#X connect 7 0 0 0;
+#X connect 8 0 4 0;
+#X connect 8 1 5 0;
+#X connect 8 2 6 0;
+#X connect 8 3 7 0;
+#X connect 9 0 8 0;
+#X restore 54 198 pd auto;
+#X text 89 15 1- set train mode;
+#X text 145 108 2- set inputs \, expected output and click "train!"
+;
+#X text 284 135 3- repeat at will;
+#X text 190 263 4- when ready set running mode again;
+#X text 211 176 NOTE: look at the second outlet to know the current
+mse after each training pattern;
+#X connect 1 0 0 0;
+#X connect 2 0 6 1;
+#X connect 3 0 6 2;
+#X connect 4 0 6 3;
+#X connect 5 0 6 0;
+#X connect 6 0 7 0;
+#X connect 7 1 8 0;
+#X connect 7 2 8 1;
+#X connect 7 3 8 2;
+#X connect 8 0 0 0;
+#X connect 9 0 0 0;
+#X connect 10 0 0 0;
+#X restore 95 104 pd train the net;
+#X text 127 21 1- create the net with 2 ins and 1 out;
+#X text 248 63 2a -train it using a train file;
+#X text 201 99 2b- or train it on-the-fly;
+#X text 193 165 3- set the filename and save it;
+#X text 119 206 4- use the net passing a list of floats;
+#X obj 89 305 nbx 8 14 -1e+037 1e+037 0 0 empty empty mse 0 -6 0 10
+-262144 -1 -1 0 256;
+#X obj 52 259 ann_mlp;
+#X connect 0 0 16 0;
+#X connect 1 0 16 0;
+#X connect 3 0 16 0;
+#X connect 4 0 16 0;
+#X connect 5 0 16 0;
+#X connect 6 0 16 0;
+#X connect 8 0 16 0;
+#X connect 9 0 16 0;
+#X connect 16 0 2 0;
+#X connect 16 1 15 0;
diff --git a/examples/ann_mlp_example2/README.txt b/examples/ann_mlp_example2/README.txt
new file mode 100755
index 0000000..d32d32d
--- /dev/null
+++ b/examples/ann_mlp_example2/README.txt
@@ -0,0 +1,32 @@
+example 2: a more complex use of ann_mlp
+
+GEM and pmpd are needed to run this example
+
+start example2.pd
+
+start GEM rendering. 
+see how the cursor is locked to the great red ball 
+and how you can push the 6 small balls.
+each small ball has associated a sine wave
+its volume = its velocity
+
+if you want to train the net using different meanings from mine
+you can write a testfile or train the net on the fly or both 
+(train on file then refine on the fly)
+
+training on the fly is simpler
+
+training is a bit tricky but might be more efficient (less error in the nn)
+
+to write a testfile:
+1)toggle ON in [pd write trainfile]
+2)record a list of patterns
+3)toggle OFF when you are ready
+4)write to a file
+5)edit the file adding a line with 3 integers
+6)change training parameters (from the defaul to more flexible ones)
+I now suggest to lower pd's process priority to normal 
+because the training process blocks pd and may slow down your computer
+7) start trainign from file. this will take a long time, 
+wait for the message in console for the training to be completed
+8) now you can activate the metro and run the net and see how it responds.
diff --git a/examples/ann_mlp_example2/cellulaSuono.pd b/examples/ann_mlp_example2/cellulaSuono.pd
new file mode 100755
index 0000000..1d8b806
--- /dev/null
+++ b/examples/ann_mlp_example2/cellulaSuono.pd
@@ -0,0 +1,195 @@
+#N canvas 139 46 648 666 10;
+#X msg 36 169 setXY \$1 \$2;
+#X obj 36 22 loadbang;
+#X obj 36 144 pack f f;
+#X obj 36 46 t b b;
+#X obj 57 246 gemhead;
+#X obj 57 269 translateXYZ;
+#X obj 46 219 unpack s f f;
+#X obj 143 24 r reset_masse;
+#X msg 36 391 setX \$1 \, setY \$2;
+#X obj 36 70 random 20;
+#X obj 36 116 / 4;
+#X obj 102 69 random 20;
+#X obj 102 115 / 4;
+#X obj 36 93 - 10;
+#X obj 102 91 - 10;
+#X obj 294 353 r link;
+#X obj 36 195 masse2D masse 100;
+#X obj 205 193 unpack s f f f;
+#X obj 189 219 unpack s f f f;
+#X obj 35 499 iCircle2D masse 0 0 1e-006 0.8 0 0 -0.05;
+#X obj 57 302 color 0.5 0 0;
+#N canvas 0 0 747 605 build 0;
+#X obj 137 30 inlet;
+#X obj 143 202 outlet;
+#X obj 144 168 pack f f f;
+#X obj 243 65 t b;
+#X msg 243 91 0;
+#X text 41 246 if input is near 0 it is a low note then i give dark
+color \, if near 1 it is a high one then give bright red color;
+#X obj 102 94 * 0.6;
+#X obj 101 123 + 0.4;
+#X obj 193 93 * -0.7;
+#X obj 193 115 + 0.7;
+#X connect 0 0 3 0;
+#X connect 0 0 6 0;
+#X connect 0 0 8 0;
+#X connect 2 0 1 0;
+#X connect 3 0 4 0;
+#X connect 4 0 2 2;
+#X connect 6 0 7 0;
+#X connect 7 0 2 0;
+#X connect 8 0 9 0;
+#X connect 9 0 2 1;
+#X restore 232 306 pd build color;
+#N canvas 444 28 999 679 sound 0;
+#X obj 77 43 inlet;
+#X obj 145 45 inlet;
+#X obj 220 44 inlet;
+#X obj 96 403 stereo;
+#X obj 249 300 osc~;
+#X obj 272 201 loadbang;
+#X obj 180 346 *~;
+#X msg 179 213 \$1 5;
+#X text 41 17 todo: invece di usare un sinusoide casuale usare un campione
+;
+#X obj 179 189 clip 0 1;
+#X obj 95 454 throw~ mainL;
+#X obj 178 454 throw~ mainR;
+#X obj 94 260 + 4;
+#X obj 94 281 / 8;
+#X obj 94 302 clip 0 1;
+#X obj 249 279 * 55;
+#X obj 179 238 line;
+#X obj 272 228 random 100;
+#X obj 272 251 tabread armoniche_caso;
+#X obj 309 456 outlet;
+#X text 387 233 weightened random values;
+#X text 385 222 which harmonic am I?;
+#X text 292 280 <-- base frequency = A;
+#X text 376 337 normalized 0-1;
+#X msg 351 186 bang;
+#X obj 309 431 clip 0 1;
+#X obj 320 386 expr sqrt($f1);
+#X obj 333 338 / 50;
+#X obj 354 143 r reset_masse;
+#X text 32 375 TODO: quadriphony;
+#X obj 184 100 - 0.001;
+#X obj 297 41 inlet;
+#X obj 249 113 sel 1 0;
+#X obj 249 94 f;
+#X obj 249 75 bang;
+#X obj 249 132 bang;
+#X obj 216 153 f;
+#X connect 0 0 12 0;
+#X connect 2 0 30 0;
+#X connect 2 0 34 0;
+#X connect 3 0 10 0;
+#X connect 3 1 11 0;
+#X connect 4 0 6 0;
+#X connect 5 0 17 0;
+#X connect 6 0 3 0;
+#X connect 7 0 16 0;
+#X connect 9 0 7 0;
+#X connect 12 0 13 0;
+#X connect 13 0 14 0;
+#X connect 14 0 3 1;
+#X connect 15 0 4 0;
+#X connect 16 0 6 1;
+#X connect 17 0 18 0;
+#X connect 18 0 15 0;
+#X connect 18 0 27 0;
+#X connect 24 0 17 0;
+#X connect 25 0 19 0;
+#X connect 26 0 25 0;
+#X connect 27 0 26 0;
+#X connect 28 0 24 0;
+#X connect 30 0 36 1;
+#X connect 31 0 33 1;
+#X connect 32 0 35 0;
+#X connect 33 0 32 0;
+#X connect 34 0 33 0;
+#X connect 35 0 36 0;
+#X connect 36 0 9 0;
+#X restore 232 285 pd sound;
+#X obj 57 339 sphere 0.3;
+#X text 294 285 make saound;
+#X text 330 304 color the cell;
+#X obj 414 99 r \$1-deactivate;
+#X obj 320 97 r \$1-activate;
+#X msg 321 131 1;
+#X msg 413 133 0;
+#X obj 327 406 sel 1 0;
+#X obj 327 380 f;
+#X obj 326 426 bang;
+#X obj 368 66 loadbang;
+#X obj 186 84 r \$1-posx;
+#X obj 228 103 r \$1-posy;
+#X obj 186 132 pack f f;
+#X obj 49 467 iCircle2D masse 0 0 1e-006 0.5 0 0 1;
+#X obj 429 284 s \$1-X;
+#X obj 509 284 s \$1-Y;
+#X obj 448 404 s \$1-Velo;
+#X obj 429 245 / 4;
+#X obj 429 264 clip -1 1;
+#X text 420 225 scale to [-1 \, 1] and send;
+#X obj 509 245 / 4;
+#X obj 509 264 clip -1 1;
+#X text 409 340 scale to [0 \, 5] and send;
+#X obj 448 360 * 50;
+#X obj 448 383 clip 0 5;
+#X connect 0 0 16 0;
+#X connect 1 0 3 0;
+#X connect 2 0 0 0;
+#X connect 3 0 9 0;
+#X connect 3 1 11 0;
+#X connect 4 0 5 0;
+#X connect 5 0 20 0;
+#X connect 6 1 5 1;
+#X connect 6 2 5 2;
+#X connect 7 0 3 0;
+#X connect 8 0 19 0;
+#X connect 8 0 37 0;
+#X connect 9 0 13 0;
+#X connect 10 0 2 0;
+#X connect 11 0 14 0;
+#X connect 12 0 2 1;
+#X connect 13 0 10 0;
+#X connect 14 0 12 0;
+#X connect 15 0 31 0;
+#X connect 16 0 6 0;
+#X connect 16 0 8 0;
+#X connect 16 0 18 0;
+#X connect 16 2 17 0;
+#X connect 17 3 22 2;
+#X connect 17 3 47 0;
+#X connect 18 1 22 0;
+#X connect 18 1 41 0;
+#X connect 18 2 22 1;
+#X connect 18 2 44 0;
+#X connect 20 0 23 0;
+#X connect 21 0 20 1;
+#X connect 22 0 21 0;
+#X connect 26 0 29 0;
+#X connect 27 0 28 0;
+#X connect 28 0 4 0;
+#X connect 28 0 31 1;
+#X connect 28 0 22 3;
+#X connect 29 0 4 0;
+#X connect 29 0 31 1;
+#X connect 29 0 22 3;
+#X connect 30 0 32 0;
+#X connect 31 0 30 0;
+#X connect 32 0 19 0;
+#X connect 32 0 37 0;
+#X connect 33 0 28 0;
+#X connect 34 0 36 0;
+#X connect 35 0 36 1;
+#X connect 36 0 0 0;
+#X connect 41 0 42 0;
+#X connect 42 0 38 0;
+#X connect 44 0 45 0;
+#X connect 45 0 39 0;
+#X connect 47 0 48 0;
+#X connect 48 0 40 0;
diff --git a/examples/ann_mlp_example2/complex.net b/examples/ann_mlp_example2/complex.net
new file mode 100755
index 0000000..c3af274
--- /dev/null
+++ b/examples/ann_mlp_example2/complex.net
@@ -0,0 +1,7 @@
+FANN_FLO_1.1
+3 0.700000 1.000000 0 5 5 5.00000000000000000000e-001 5.00000000000000000000e-001
+21 4 5 
+0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
+21 21 21 0 
+4 4 4 4 0 
+(0 1.25349550000000000000e+007) (1 -3.52599375000000000000e+006) (2 6.53671600000000000000e+006) (3 2.00417740000000000000e+007) (4 7.30595800000000000000e+006) (5 1.43338820000000000000e+007) (6 -1.64091900000000000000e+007) (7 2.72516540000000000000e+007) (8 8.50143700000000000000e+006) (9 1.94773520000000000000e+007) (10 1.37618080000000000000e+007) (11 9.89361400000000000000e+006) (12 -1.62668140000000000000e+007) (13 1.19877080000000000000e+007) (14 1.38944980000000000000e+007) (15 1.55818800000000000000e+007) (16 -4.50917906250000000000e+005) (17 1.43993210000000000000e+007) (18 1.17652580000000000000e+007) (19 -8.81434000000000000000e+006) (20 -6.01233154296875000000e+002) (0 9.62663600000000000000e+006) (1 -1.60156980000000000000e+007) (2 3.24279360000000000000e+007) (3 2.48126960000000000000e+007) (4 -3.12803475000000000000e+006) (5 3.24320160000000000000e+007) (6 2.56624260000000000000e+007) (7 -2.17010500000000000000e+006) (8 3.24311700000000000000e+007) (9 1.77973300000000000000e+006) (10 7.12998450000000000000e+006) (11 3.24320600000000000000e+007) (12 -6.82372550000000000000e+006) (13 1.10809970000000000000e+007) (14 3.24223120000000000000e+007) (15 1.30904130000000000000e+007) (16 2.12644620000000000000e+007) (17 3.24279100000000000000e+007) (18 3.88056600000000000000e+006) (19 3.25780950000000000000e+006) (20 5.93454052734375000000e+003) (0 -1.02708820000000000000e+007) (1 1.92679760000000000000e+007) (2 2.48948700000000000000e+007) (3 -2.26269800000000000000e+007) (4 1.61687180000000000000e+007) (5 2.51848860000000000000e+007) (6 -2.32199250000000000000e+006) (7 1.89744400000000000000e+007) (8 2.57103520000000000000e+007) (9 -1.62862460000000000000e+007) (10 -7.64894750000000000000e+005) (11 2.58289860000000000000e+007) (12 -1.44739700000000000000e+007) (13 9.75394900000000000000e+006) (14 2.50721400000000000000e+007) (15 -1.48601670000000000000e+007) (16 9.29974700000000000000e+006) (17 2.55408640000000000000e+007) (18 6.27725250000000000000e+005) (19 3.43336175000000000000e+006) (20 -6.19121948242187500000e+002) (21 -2.33448815345764160000e+000) (22 -2.11909532546997070000e-001) (23 1.17793101817369460000e-002) (24 2.53461837768554690000e+000) (21 2.28352487087249760000e-001) (22 3.55203837156295780000e-001) (23 -1.76965391635894780000e+000) (24 1.18609762191772460000e+000) (21 8.16280126571655270000e-001) (22 1.02861607074737550000e+000) (23 1.21739065647125240000e+000) (24 5.82793474197387700000e-001) (21 -8.56908917427062990000e-001) (22 4.63776290416717530000e-001) (23 -1.62467598915100100000e+000) (24 2.01780867576599120000e+000) 
diff --git a/examples/ann_mlp_example2/complex.txt b/examples/ann_mlp_example2/complex.txt
new file mode 100755
index 0000000..77bafa6
--- /dev/null
+++ b/examples/ann_mlp_example2/complex.txt
@@ -0,0 +1,513 @@
+255 20 4
+0.749041 0.0896327 0.113853 0.654362 0.185624 0.237424 0.69533 0.298684 0.0945817 0.787286 0.213076 0.20047 0.63797 0.0635322 0.115899 0.759821 -0.061697 0.0982502 3.712 0.336
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diff --git a/examples/ann_mlp_example2/example2.pd b/examples/ann_mlp_example2/example2.pd
new file mode 100755
index 0000000..9cd588e
--- /dev/null
+++ b/examples/ann_mlp_example2/example2.pd
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+#X text 39 39 <- begin (change the metro speed for slow computer);
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+#X text 337 49 example "stolen" from pmpd examples. move the main cell
+with your mouse (or via osc) every cell is a random harmonic of A (from
+1st to 50th) \, the velo of a cell is its volume also.;
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+#X msg 247 324 load conplex.net;
+#X text 148 15 1- create the ann;
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+#X msg 198 224 train-on-file complex.txt;
+#X text 200 242 training on files with many patterns may take minutes
+\, please be patient.;
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+#X msg 77 135 max_iterations 200000;
+#X text 69 76 due to the complexity of the input and output data you
+should change the default training parameters:;
+#X text 219 134 smaller cycle;
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+#X text 66 77 here go the outputs;
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+#X text 156 406 todo: write header (a line at the beginning of file
+with 3 int: how many tests \, num_input \, num_output);
+#X obj 122 190 delay 50;
+#X obj 115 159 metro 100;
+#X floatatom 346 70 5 100 5000 2 msec_between_snapshots - -;
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+-1 0 1;
+#X obj 219 189 / 2;
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+#X text 293 224 comment;
+#N canvas 262 68 635 591 README 0;
+#X text 11 63 how to use: 1) modify [pd inputs] and [ps outputs] inserting
+[r] objects to receive input data \, and modify [pack]s to handle the
+right number of inputs 2) do the same with [pd outputs] 3) click on
+reset 4) toggle ON and start collectng data 5) when you are ready toggle
+OFF 6) edit [write filename cr( with the actual filename you want for
+your training data (always keep the cr after the filename) 7) open
+the file with training data 8) add a line at the beginning and write
+3 integers: the 1st is the number of training dataset written (see
+"how many datasets" number box) \, the 2nd is how many inputs your
+ann has \, the 3th is how many outputs e.g. i collected 100 training
+snapshots \, for a ann with 10 ins and 2 outs I write: 100 10 2 at
+the very beginning of the file now the training file is ready and can
+be read from nn via train-on-file command;
+#X text 143 489 please help me getting this patch more usable: - how
+to add a line at the very beginning of a text file after i have filled
+it? - how to manage inputs and outputs of different sized without forcing
+the user to edit the patch?;
+#X text 9 7 this tricky patch is usefull to write a file to train ann
+and is intended to be used with the nn external;
+#X restore 33 13 pd README;
+#X text 516 7 by davide morelli info@davidemorelli.it;
+#X text 106 14 <--readme!;
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+#X text 431 270 sx;
+#X text 496 272 dx;
+#X text 566 269 chaos;
+#X text 635 269 calm;
+#X text 434 171 4 outputs: using keyboard: asdf: a=sx-ness \, s=dx-ness
+\, d=chaos-ness \, f=calm-ness;
+#X text 363 348 remember to add a line at the beginning of the file
+with 3 integers... how_many_patterns 20 4 ...see README;
+#X text 142 308 <--we have 20 inputs;
+#X text 242 283 <--we have 4 outputs;
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+#X restore 40 27 pd write trainfile;
+#X text 163 28 1- write a trainfile;
+#X text 69 63 2- adjust parameters before training;
+#X text 225 205 3- train on the file;
+#X text 195 110 higher error allowed;
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+#X text 217 70 2a- train using a file or;
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+#X text 128 14 1- change to training mode;
+#X text 204 49 2- change keys if you want;
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+#X text 239 182 3- toggle on to start training and off to stop;
+#X msg 170 282 run;
+#X text 200 283 4- switch to run mode when ready;
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+#X restore 133 114 pd train on the fly;
+#X text 255 113 2b- train on the fly in realtime;
+#X text 224 182 3- run the nn switching this metro ON;
+#X text 277 213 (note \, you must be in run mode);
+#X msg 281 231 run;
+#X text 34 403 left;
+#X text 75 404 right;
+#X text 356 305 4- when you are happy with you nn save it;
+#X text 354 323 remember that you can load it also passing filename
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+#X text 101 12 1- start rendering;
+#X text 141 142 2- open the subpatch and follow instructions;
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+#X text 329 -7 usando la formula (x*x);
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+#X text 31 23 this abstraction splits one signal into a 2 channels
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+#X text 115 137 info@davidemorelli.it;
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+#X text 224 182 3- run the nn switching this metro ON;
+#X text 277 213 (note \, you must be in run mode);
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+#X text 364 303 4- when you are happy with you nn save it;
+#X text 362 321 remember that you can load it also passing filename
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+#X msg 66 15 create 10 4;
+#X msg 247 306 save tdnn.net;
+#X msg 247 325 load tdnn.net;
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+#X text 93 61 1- start rendering;
+#X text 71 170 2- open the subpatch and follow instructions;
+#X text 15 5 TDNN implementation (Time Delay Neural Network) useful
+for gesture recognition;
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diff --git a/examples/ann_mlp_example3/tdnn.net b/examples/ann_mlp_example3/tdnn.net
new file mode 100755
index 0000000..6c9540d
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+++ b/examples/ann_mlp_example3/tdnn.net
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author	Davide Morelli <morellid@users.sourceforge.net>	2005-05-18 15:55:28 +0000
committer	Davide Morelli <morellid@users.sourceforge.net>	2005-05-18 15:55:28 +0000
commit	f64944ede13a3f95e9ad3130c74a53833f1a04bf (patch)
tree	398a9486fc77bc1a7308f94fd048f56963c6e48e
parent	4c962acc9f2b6e275f02ab7660a8471453c2f393 (diff)