From 2bc706c452393b3a1e0258990d2d3f9242a6b0a2 Mon Sep 17 00:00:00 2001 From: Georg Holzmann Date: Fri, 5 Jan 2007 16:39:00 +0000 Subject: changing to new helpfile format svn path=/trunk/externals/grh/; revision=7214 --- adaptive/doc/help-nlms~.pd | 186 --------------------------------------------- 1 file changed, 186 deletions(-) delete mode 100755 adaptive/doc/help-nlms~.pd (limited to 'adaptive/doc/help-nlms~.pd') diff --git a/adaptive/doc/help-nlms~.pd b/adaptive/doc/help-nlms~.pd deleted file mode 100755 index d58ef68..0000000 --- a/adaptive/doc/help-nlms~.pd +++ /dev/null @@ -1,186 +0,0 @@ -#N canvas 0 0 700 667 10; -#X msg 395 342 getmu; -#X msg 395 321 mu \$1; -#X floatatom 403 302 8 0 0 0 - - -; -#X msg 395 450 getN; -#X msg 395 539 help; -#X msg 395 199 clear; -#X msg 395 266 print; -#X floatatom 37 406 8 0 0 0 - - -; -#X msg 395 507 read demo.dat; -#X msg 395 163 getadaptation; -#X obj 395 120 tgl 15 0 empty empty empty 0 -6 0 8 -262144 -1 -1 0 -1; -#X msg 395 141 adaptation \$1; -#X msg 395 486 write demo.dat; -#X obj 45 320 r message; -#X obj 395 568 s message; -#N canvas 0 0 260 260 unsig~ 0; -#X obj 22 42 inlet~; -#X text 62 42 ~signal_in~; -#X obj 22 168 outlet; -#X text 69 169 float-out; -#X obj 22 142 snapshot~; -#X obj 39 119 metro 300; -#X obj 40 70 loadbang; -#X msg 40 95 1; -#X connect 0 0 4 0; -#X connect 4 0 2 0; -#X connect 5 0 4 0; -#X connect 6 0 7 0; -#X connect 7 0 5 0; -#X restore 37 384 pd unsig~; -#X text 89 260 input signal x[n]; -#X text 177 287 reference signal d[n]; -#X text 177 302 (desired signal); -#X text 108 385 output signal y[n]; -#X text 35 172 init arg1: nr. of coefficients; -#X text 498 141 turn adaptation on/off; -#X text 443 193 clear current coefficients; -#X text 443 206 and set them back to 0; -#X text 444 265 print current coefficients; -#X text 35 185 init arg2: stepsize parameter mu; -#X text 446 325 set/get stepsize parameter; -#X text 447 339 mu (learning rate); -#X text 436 450 get Nr. of coefficients; -#X text 506 503 and mu to file; -#X text 506 489 write/read coefficients; -#X text 206 622 (c) Georg Holzmann \, 2005; -#X text 36 481 some more info:; -#X obj 219 24 cnv 15 258 58 empty empty empty 10 22 0 14 -1 -66577 -0; -#X obj 223 28 cnv 15 250 50 empty empty nlms~ 10 24 0 14 -228992 -1 -0; -#X text 350 38 adaptive systems; -#X text 360 54 for Pure Data; -#X text 34 562 in the example folder !; -#X text 35 548 For much more examples see patches; -#X obj 38 259 sig~ 2; -#X obj 125 286 sig~ 1; -#X text 36 134 Normalized LMS: normalized least mean square; -#X text 146 147 adaptation algorithm; -#N canvas 347 29 502 539 NLMS_EXPLANATION 0; -#X text 35 135 x[n] ... input signal of the system; -#X text 35 120 c[n] ... coefficient vector of the system; -#X text 35 104 y[n] ... output signal of the system; -#X text 35 398 d[n] ... desired signal \, reference signal; -#X text 50 74 -> y[n] = c0[n]*x[n] + c1[n]*x[n-1] + c2[n]*x[n-2] + -...; -#X text 35 312 mu ... step-size parameter (learning rate); -#X text 34 282 c[n] ... new coefficient vector; -#X text 34 297 c[n-1] ... old coefficient vector; -#X text 34 354 e[n] ... error sample at time n \, LMS tries to minimize -this error; -#X text 35 382 x[n] ... tap-input vector at time n; -#X text 71 241 with e[n] = d[n] - y[n]; -#X text 33 33 An adaptive system is simply a FIR filter with the coefficients -c[n] \, which can be learned.; -#X text 36 440 How to choose mu ?; -#X text 36 463 Sufficient (deterministic) stability condition:; -#X text 32 195 The normalized LMS Adaptation Algorithm:; -#X text 70 226 c[n] = c[n-1] + mu/(alpha+abs(x[n])^2) *e[n]*x[n]; -#X text 34 327 alpha ... a small positive constant \, only to avoid -division by zero; -#X text 152 490 0 < mu < 2; -#X restore 38 503 pd NLMS_EXPLANATION; -#N canvas 536 326 510 502 NLMS_EXAMPLE 0; -#X obj 31 109 sig~ 2; -#X obj 116 111 sig~ 1; -#X text 36 87 x[n]; -#X text 124 92 d[n]; -#X text 31 234 y[n]; -#X text 115 28 x[n] = 2 \, d[n] = 1 \, N = 1 (= nr. of coefficients) -; -#X text 26 29 EXAMPLE:; -#N canvas 0 0 450 300 graph3 0; -#X array x 1024 float 0; -#X array y 1024 float 0; -#X array d 1024 float 0; -#X coords 0 2 1023 0 400 140 1; -#X restore 51 302 graph; -#N canvas 422 247 725 220 plot_logic 0; -#X obj 72 168 tabwrite~ x; -#X obj 158 168 tabwrite~ y; -#X obj 244 168 tabwrite~ d; -#X obj 191 105 metro 100; -#X obj 191 54 loadbang; -#X msg 191 80 1; -#X obj 386 57 loadbang; -#X obj 72 142 r~ x_; -#X obj 158 142 r~ y_; -#X obj 244 142 r~ d_; -#X msg 362 153 \; x yticks 0 0.25 2; -#X msg 346 121 \; x xticks 0 32 2; -#X msg 503 150 \; x ylabel 1060 0 0.5 1 1.5 2; -#X msg 479 105 \; x xlabel -0.2 0 256 512 768 1024; -#X connect 3 0 0 0; -#X connect 3 0 1 0; -#X connect 3 0 2 0; -#X connect 4 0 5 0; -#X connect 5 0 3 0; -#X connect 6 0 11 0; -#X connect 6 0 10 0; -#X connect 6 0 13 0; -#X connect 6 0 12 0; -#X connect 7 0 0 0; -#X connect 8 0 1 0; -#X connect 9 0 2 0; -#X restore 198 246 pd plot_logic; -#X msg 341 220 adaptation 1; -#X obj 341 199 loadbang; -#X msg 198 171 mu \$1; -#X floatatom 210 150 8 0 0 0 - - -; -#X text 275 147 <- try different mu; -#X msg 199 109 clear; -#X text 242 110 <- clear to start new adaptation; -#X text 189 461 -- 1024 samples --; -#X obj 37 131 s~ x_; -#X obj 125 133 s~ d_; -#X obj 31 213 s~ y_; -#X obj 40 159 r \$0-nlms; -#X obj 198 207 s \$0-nlms; -#X obj 341 244 s \$0-nlms; -#X obj 30 181 nlms~ 1 0.001; -#X connect 0 0 17 0; -#X connect 0 0 23 0; -#X connect 1 0 18 0; -#X connect 1 0 23 1; -#X connect 9 0 22 0; -#X connect 10 0 9 0; -#X connect 11 0 21 0; -#X connect 12 0 11 0; -#X connect 14 0 21 0; -#X connect 20 0 23 0; -#X connect 23 0 19 0; -#X restore 38 525 pd NLMS_EXAMPLE; -#X floatatom 403 372 8 0 0 0 - - -; -#X msg 395 391 alpha \$1; -#X msg 395 412 getalpha; -#X text 464 393 set/get alpha (normally; -#X text 465 407 you don't need that); -#X obj 38 345 nlms~ 2 0.001; -#X msg 395 236 init_unity; -#X text 475 223 set first coefficient to 1 \,; -#X text 477 236 all others to 0 (= delay; -#X text 476 249 free transmission); -#X connect 0 0 14 0; -#X connect 1 0 14 0; 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