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diff --git a/adaptive/doc/nlms~-help.pd b/adaptive/doc/nlms~-help.pd new file mode 100755 index 0000000..d58ef68 --- /dev/null +++ b/adaptive/doc/nlms~-help.pd @@ -0,0 +1,186 @@ +#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 <grh@mur.at> \, 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; +#X connect 2 0 1 0; +#X connect 3 0 14 0; +#X connect 4 0 14 0; +#X connect 5 0 14 0; +#X connect 6 0 14 0; +#X connect 8 0 14 0; +#X connect 9 0 14 0; +#X connect 10 0 11 0; +#X connect 11 0 14 0; +#X connect 12 0 14 0; +#X connect 13 0 50 0; +#X connect 15 0 7 0; +#X connect 39 0 50 0; +#X connect 40 0 50 1; +#X connect 45 0 46 0; +#X connect 46 0 14 0; +#X connect 47 0 14 0; +#X connect 50 0 15 0; +#X connect 51 0 14 0; 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