• API
• FAQ
• Tools
• Archive
SHARE
TWEET

# Responsi SinyL

a guest Jun 25th, 2019 62 Never
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
1. fs = 10000;
2. f= 60;
3. t = 0:1/fs:4;
4. x =4*sin(2*pi*f*t);
5. y =4*square(2*pi*f*t);
6. z =4*sawtooth(2*pi*f*t);
7. plot (t,x);
8. axis ([0 0.1 -5 5])
9.
10. _______________________________________
11. %Frekuensi Sampling
12. f=35+10;
13. fsa=1000;
14. fsb=10000;
15. fsc=50;
16. fsd=2.01*f;
17. fse=2.1*f;
18. fsf=1.9*f;
19.
20. %Periode
21. ta= 0:1/fsa:1;
22. tb= 0:1/fsb:1;
23. tc= 0:1/fsc:1;
24. td= 0:1/fsd:1;
25. te= 0:1/fse:1;
26. tf= 0:1/fsf:1;
27.
28. %Signal Equetion
29. Sinyal_a= sin(2*pi*f*ta);
30. Sinyal_b= sin(2*pi*f*tb);
31. Sinyal_c= sin(2*pi*f*tc);
32. Sinyal_d= sin(2*pi*f*td);
33. Sinyal_e= sin(2*pi*f*te);
34. Sinyal_f= sin(2*pi*f*tf);
35.
36. fsg= [10:0.1:200];
37. for i = 1:length (fsg)
38.         tg= 0:1/fsg(i):1;
39.         Sinyal_g = sin(2*pi*f*tg);
40.         pks_g(i) =length(findpeaks(Sinyal_g));
41. end
42.
43. %Plotting Sinyal
44. figure(1)
45. subplot(3,2,1);
46. plot(ta,Sinyal_a)
47. title('Sinyal Frekuensi 1000 HZ');
48. xlabel('Time(s)')
49. ylabel('Amplitude');
50. subplot(3,2,2);
51. plot(tb,Sinyal_b)
52. title('Sinyal Frekuensi 10000 Hz');
53. xlabel('Time(s)')
54. ylabel('Amplitude');
55. subplot(3,2,3);
56. plot(tc,Sinyal_c)
57. title('Sinyal Frekuensi 50 Hz');
58. xlabel('Time(s)')
59. ylabel('Amplitude');
60. subplot(3,2,4);
61. plot(td,Sinyal_d)
62. title('Sinyal Frekuensi 90.45 Hz');
63. xlabel('Time(s)')
64. ylabel('Amplitude');
65. subplot(3,2,5);
66. plot(te,Sinyal_e)
67. title('Sinyal Frekuensi 94.5 Hz');
68. xlabel('Time(s)')
69. ylabel('Amplitude');
70. subplot(3,2,6);
71. plot(tf,Sinyal_f)
72. title('Sinyal Frekuensi 85.5 Hz');
73. xlabel('Time(s)')
74. ylabel('Amplitude');
75.
76. figure (2)
77.
78. subplot(3,2,1);
79. plot(ta,Sinyal_a)
80. title('Sinyal Frekuensi 1000 HZ');
81. xlabel('Time(s)')
82. ylabel('Amplitude');
83. findpeaks(Sinyal_a,ta)
84. pks_a = findpeaks(Sinyal_a,ta);
85.
86. subplot(3,2,2);
87. plot(tb,Sinyal_b)
88. title('Sinyal Frekuensi 10000 Hz');
89. xlabel('Time(s)')
90. ylabel('Amplitude');
91. findpeaks(Sinyal_b,tb)
92. pks_b = findpeaks(Sinyal_b,tb);
93.
94. subplot(3,2,3);
95. plot(tc,Sinyal_c)
96. title('Sinyal Frekuensi 50 Hz');
97. xlabel('Time(s)')
98. ylabel('Amplitude');
99. findpeaks(Sinyal_c,tc)
100. pks_c = findpeaks(Sinyal_c,tc);
101.
102. subplot(3,2,4);
103. plot(td,Sinyal_d)
104. title('Sinyal Frekuensi 90.45 Hz');
105. xlabel('Time(s)')
106. ylabel('Amplitude');
107. findpeaks(Sinyal_d,td)
108. pks_d = findpeaks(Sinyal_d,td);
109.
110. subplot(3,2,5);
111. plot(te,Sinyal_e)
112. title('Sinyal Frekuensi 94.5 Hz');
113. xlabel('Time(s)')
114. ylabel('Amplitude');
115. subplot(3,2,6);
116. findpeaks(Sinyal_e,te)
117. pks_e = findpeaks(Sinyal_e,te);
118.
119. plot(tf,Sinyal_f)
120. title('Sinyal Frekuensi 85.5 Hz');
121. xlabel('Time(s)')
122. ylabel('Amplitude');
123. findpeaks(Sinyal_f,tf)
124. pks_f = findpeaks(Sinyal_f,tf);
125.
126.
127. figure (3)
128. plot(fsg,pks_g)
129. findpeaks(pks_g,fsg)
130. title('Sinyal Fg');
131. xlabel('Time(s)')
132. ylabel('Amplitude');
133.
134.
135. __________________________
136.
137.
138. %Frekuensi
139. f = 60;
140. %Deskrit
141. D = [ 6, 4, 5, 6, 1, 2, 2, 5]
142. %Impulse
143. I = [ones(1,1), zeros(1,7)]
144. %Sampling
145. fs = 1000;
146. %Time index
147. t1 = 0:1/fs:4;
148. t2 = 0:14;
149. t3 = 0:4007;
150. t4 = 0:8000;
151. %Fungsi sinyal
152. MySignal1 = 3*sawtooth(2*pi*f*t1)
153. MySignal2 = 5*square(2*pi*f*t1);
154. MySignal3 = 8*square(2*pi*f*t1);
155.
156. %Convolution
157. CSignal1 = conv(D,I)
158. CSignal2 = conv(D,MySignal1)
159. CSignal3 = conv(D,MySignal2)
160. CSignal4 = conv(D,MySignal3)
161. CSignal5 = conv(I,MySignal2)
162. CSignal6 = conv(I,MySignal1)
163. CSignal7 = conv(I,MySignal3)
164. CSignal8 = conv(MySignal1,MySignal2)
165. CSignal9 = conv(MySignal2,MySignal3)
166.
167. %Plotting Sinyal
168. figure(1)
169. subplot(2,2,1);
170. %plot(t2,CSignal1)
171. stem(t2,CSignal1);
172. xlim([0 16])
173. title('Discrete + Impulse Signal');
174. xlabel('Time(s)')
175. ylabel('Amplitude');
176. subplot(2,2,2);
177. %plot(t3,CSignal2)
178. stem(t3,CSignal2);
179. xlim([0 16])
180. title('Discrete + Sawtooth Signal');
181. xlabel('Time(s)')
182. ylabel('Amplitude');
183. subplot(2,2,3);
184. %plot(t3,CSignal3)
185. stem(t3,CSignal3);
186. xlim([0 16])
187. title('Discrete + Square Signal');
188. xlabel('Time(s)')
189. ylabel('Amplitude');
190. subplot(2,2,4);
191. %plot(t3,CSignal4)
192. stem(t3,CSignal4);
193. xlim([0 16])
194. title('Discrete + My Signal');
195. xlabel('Time(s)')
196. ylabel('Amplitude');
197. figure(2)
198. subplot(3,2,1);
199. %plot(t3,CSignal5)
200. stem(t3,CSignal5);
201. xlim([0 16])
202. title('Impulse + Square Signal');
203. xlabel('Time(s)')
204. ylabel('Amplitude');
205. subplot(3,2,2);
206. %plot(t3,CSignal6)
207. stem(t3,CSignal6);
208. xlim([0 16])
209. title('Impulse + Sawtooth Signal');
210. xlabel('Time(s)')
211. ylabel('Amplitude');
212. subplot(3,2,3);
213. %plot(t3,CSignal7)
214. stem(t3,CSignal7);
215. xlim([0 16])
216. title('Impulse + My Signal');
217. xlabel('Time(s)')
218. ylabel('Amplitude');
219. subplot(3,2,4);
220. %plot(t4,CSignal8)
221. stem(t4,CSignal8);
222. xlim([0 16])
223. title('Square + Sawtooth Signal');
224. xlabel('Time(s)')
225. ylabel('Amplitude');
226. subplot(3,2,5);
227. %plot(t4,CSignal9)
228. stem(t4,CSignal9);
229. xlim([0 16])
230. title('Square + My Signal');
231. xlabel('Time(s)')
232. ylabel('Amplitude');
233.
234. _________________________________
235.
236. %0
237. Fs= 1000;
238. T= 1/Fs;
239. L= 1000;
240. t= (0:L-1)*T;
241. An0= 0;
242.
243. x= 0.7*sin(2*pi*50*t) + sin(2*pi*120*t);
244. y0= x + An0*randn(size(t));
245.
246. NFFT= 2^nextpow2(L);
247. Y0= fft(y0,NFFT)/L;
248. f= Fs/2*linspace(0,1,NFFT/2+1);
249.
250. %1
251. An1= 1;
252.
253. y1= x + An1*randn(size(t));
254. Y1= fft(y1,NFFT)/L;
255.
256. %2
257. An2= 2;
258.
259. y2= x + An2*randn(size(t));
260. Y2= fft(y2,NFFT)/L;
261.
262. %3
263. An3= 3;
264.
265. y3= x + An3*randn(size(t));
266. Y3= fft(y3,NFFT)/L;
267.
268. %4
269. An4= 4;
270.
271.
272. y4= x + An4*randn(size(t));
273. Y4= fft(y4,NFFT)/L;
274.
275. %5
276. An5= 5;
277.
278.
279. y5= x + An5*randn(size(t));
280. Y5= fft(y5,NFFT)/L;
281.
282. figure(1)
283. %0
284. subplot(3,2,1);
285. plot(Fs*t(1:50), y0(1:50))
286. title('Signal Corruped with Zero-Mean Random Noise')
287. xlabel('time (Miliseconds)')
288.
289. subplot(3,2,2);
290. plot(f,2*abs(Y0(1:NFFT/2+1)))
291. title('Single-side Amplitude Spectrum of y(t)')
292. ylabel('|Y (f)|')
293.
294. %1
295. subplot(3,2,3);
296. plot(Fs*t(1:50), y1(1:50))
297. title('Signal Corruped with Zero-Mean Random Noise')
298. xlabel('time (Miliseconds)')
299.
300. subplot(3,2,4);
301. plot(f,2*abs(Y1(1:NFFT/2+1)))
302. title('Single-side Amplitude Spectrum of y(t)')
303. ylabel('|Y (f)|')
304.
305. %2
306. subplot(3,2,5);
307. plot(Fs*t(1:50), y2(1:50))
308. title('Signal Corruped with Zero-Mean Random Noise')
309. xlabel('time (Miliseconds)')
310.
311. subplot(3,2,6);
312. plot(f,2*abs(Y2(1:NFFT/2+1)))
313. title('Single-side Amplitude Spectrum of y(t)')
314. ylabel('|Y (f)|')
315.
316. figure(2)
317. %3
318. subplot(3,2,1);
319. plot(Fs*t(1:50), y3(1:50))
320. title('Signal Corruped with Zero-Mean Random Noise')
321. xlabel('time (Miliseconds)')
322.
323. subplot(3,2,2);
324. plot(f,2*abs(Y3(1:NFFT/2+1)))
325. title('Single-side Amplitude Spectrum of y(t)')
326. ylabel('|Y (f)|')
327.
328. %4
329. subplot(3,2,3);
330. plot(Fs*t(1:50), y4(1:50))
331. title('Signal Corruped with Zero-Mean Random Noise')
332. xlabel('time (Miliseconds)')
333.
334. subplot(3,2,4);
335. plot(f,2*abs(Y4(1:NFFT/2+1)))
336. title('Single-side Amplitude Spectrum of y(t)')
337. ylabel('|Y (f)|')
338.
339. %5
340. subplot(3,2,5);
341. plot(Fs*t(1:50), y5(1:50))
342. title('Signal Corruped with Zero-Mean Random Noise')
343. xlabel('time (Miliseconds)')
344.
345. subplot(3,2,6);
346. plot(f,2*abs(Y5(1:NFFT/2+1)))
347. title('Single-side Amplitude Spectrum of y(t)')
348. ylabel('|Y (f)|')
349.
350.
351. -------------------------------------------------------------
352.
353. %0
354. Fs= 1000;
355. T= 1/Fs;
356. L= 1000;
357. t= (0:L-1)*T;
358. An0= 0;
359.
360. x= 0.7*sin(2*pi*50*t) + sin(2*pi*120*t);
361. y0= x + An0*randn(size(t));
362.
363. NFFT= 2^nextpow2(L);
364. Y0= fft(y0,NFFT)/L;
365. f= Fs/2*linspace(0,1,NFFT/2+1);
366.
367. %1
368. An1= 1;
369.
370. y1= x + An1*randn(size(t));
371. Y1= fft(y1,NFFT)/L;
372.
373. %2
374. An2= 2;
375.
376. y2= x + An2*randn(size(t));
377. Y2= fft(y2,NFFT)/L;
378.
379. %3
380. An3= 3;
381.
382. y3= x + An3*randn(size(t));
383. Y3= fft(y3,NFFT)/L;
384.
385. %4
386. An4= 4;
387.
388.
389. y4= x + An4*randn(size(t));
390. Y4= fft(y4,NFFT)/L;
391.
392. %5
393. An5= 5;
394.
395.
396. y5= x + An5*randn(size(t));
397. Y5= fft(y5,NFFT)/L;
398.
399. figure(1)
400. %0
401. subplot(3,2,1);
402. plot(Fs*t(1:50), y0(1:50))
403. title('Signal Corruped with Zero-Mean Random Noise')
404. xlabel('time (Miliseconds)')
405.
406. subplot(3,2,2);
407. plot(f,2*abs(Y0(1:NFFT/2+1)))
408. title('Single-side Amplitude Spectrum of y(t)')
409. ylabel('|Y (f)|')
410.
411. %1
412. subplot(3,2,3);
413. plot(Fs*t(1:50), y1(1:50))
414. title('Signal Corruped with Zero-Mean Random Noise')
415. xlabel('time (Miliseconds)')
416.
417. subplot(3,2,4);
418. plot(f,2*abs(Y1(1:NFFT/2+1)))
419. title('Single-side Amplitude Spectrum of y(t)')
420. ylabel('|Y (f)|')
421.
422. %2
423. subplot(3,2,5);
424. plot(Fs*t(1:50), y2(1:50))
425. title('Signal Corruped with Zero-Mean Random Noise')
426. xlabel('time (Miliseconds)')
427.
428. subplot(3,2,6);
429. plot(f,2*abs(Y2(1:NFFT/2+1)))
430. title('Single-side Amplitude Spectrum of y(t)')
431. ylabel('|Y (f)|')
432.
433. figure(2)
434. %3
435. subplot(3,2,1);
436. plot(Fs*t(1:50), y3(1:50))
437. title('Signal Corruped with Zero-Mean Random Noise')
438. xlabel('time (Miliseconds)')
439.
440. subplot(3,2,2);
441. plot(f,2*abs(Y3(1:NFFT/2+1)))
442. title('Single-side Amplitude Spectrum of y(t)')
443. ylabel('|Y (f)|')
444.
445. %4
446. subplot(3,2,3);
447. plot(Fs*t(1:50), y4(1:50))
448. title('Signal Corruped with Zero-Mean Random Noise')
449. xlabel('time (Miliseconds)')
450.
451. subplot(3,2,4);
452. plot(f,2*abs(Y4(1:NFFT/2+1)))
453. title('Single-side Amplitude Spectrum of y(t)')
454. ylabel('|Y (f)|')
455.
456. %5
457. subplot(3,2,5);
458. plot(Fs*t(1:50), y5(1:50))
459. title('Signal Corruped with Zero-Mean Random Noise')
460. xlabel('time (Miliseconds)')
461.
462. subplot(3,2,6);
463. plot(f,2*abs(Y5(1:NFFT/2+1)))
464. title('Single-side Amplitude Spectrum of y(t)')
465. ylabel('|Y (f)|')
466.
467.
468. ______________________________________________
469.
470.
471. fs = 10000;
472. f= 60;
473. t = 0:1/fs:4;
474. y =4*square(2*pi*f*t);
475.
476.
477. NFFT= 2^nextpow2(L);
478. Y= fft(y,NFFT)/L;
479. ff= Fs/2*linspace(0,1,NFFT/2+1);
480.
481. plot(ff,2*abs(Y(1:NFFT/2+1)))
482. title('Single-side Amplitude Spectrum of y(t)')
483. ylabel('|Y (ff)|')
484.
485. ___________________________________________
486.
487.
489. B= A(:,1);
490.
491. NFFT= 2^nextpow2(L);
492. Y= fft(B,NFFT)/L;
493. ff= Fs/2*linspace(0,1,NFFT/2+1);
494.
495. plot(ff,2*abs(Y(1:NFFT/2+1)))
496. title('Single-side Amplitude Spectrum of y(t)')
497. ylabel('|Y (f)|')
498.
499. _______________________________________
500.
501.
502. Laplace Transform and Bode Plot
503.
504. %Untuk men set sumbu X dalam Hz
505. opts = bodeoptions;
506. opts.FreqUnits = 'Hz';
507. % untuk menset fungsi transfer
508. % untuk tf([polynomial penyebut],[polynomial pembagi])
509. G1 = tf([1],[0.001 1]) %Vc(s)/Vs(s)
510. G2 = tf([-10^9-10^6 10^9],[10^3 10^6 0]) %Vr(s)/Vs(s)
511. % untuk memplot bode plot
512. figure(1)
513. bode(G1,opts)
514. grid on
515. figure(2)
516. bode(G2,opts)
517. grid on
518.
519. ____________________________________________
520.
521. Transformasi Z
522.
523. %18035(NIM 5 Digit Terakhir) x 3 = 54105
524. %Ganti Semua 0 mejadi 1, 0=>1, =54115
525. NIM_5_Digit= [5 4 1 1 5];
526. NIM = NIM_5_Digit *0.2;
527.
528. A=NIM(1,1);
529. B=NIM(1,2);
530. C=NIM(1,3);
531. D=NIM(1,4);
532. E=NIM(1,5);
533.
534. %Tugas
535. %1.
536. x1 = [1 zeros(1,100)];
537. y1 = [0 0];
538. for i = 1:length(x1)
539. n1 = i+2;
540. y1(n1) = C*x1(i) + (-1*D*y1(n1-1)) + E*y1(n1-2);
541. end
542. y1 = y1(3:n1);
543.
544. figure(1)
545. subplot(3,1,1)
546. stem(y1)
547. title('Respon Impulse sistem')
548.
549. subplot(3,1,2)
550. m1 = 100; %jumlah sample
551. BB1 = [1 0 0]; %numerator
552. AA1 = [C -D E]; %denominator
553. impz(BB1,AA1,m1)
554.
555. [Z1,P1,K1] = tf2zp(BB1,AA1)
556.
557. subplot(3,1,3)
558. zplane(BB1,AA1)
559.
560. %2.
561. x2 = [1 zeros(1,100)];
562. y2 = [0 0];
563. for i = 1:length(x2)
564. n2 = i+2;
565. y2(n2) = x2(i)+((C+(-E))*y2(n2-1));
566. end
567. y2 = y2(3:n2);
568.
569. figure(2)
570. subplot(3,1,1)
571. stem(y2)
572. title('Respon Impulse sistem')
573.
574. subplot(3,1,2)
575. m2 = 100; %jumlah sample
576. BB2 = [1 0 0]; %numerator
577. AA2 = [1 C-E 0]; %denominator
578. impz(BB2,AA2,m2)
579.
580. [Z2,P2,K2] = tf2zp(BB2,AA2)
581.
582. subplot(3,1,3)
583. zplane(BB2,AA2)
584.
585. %3
586. x3 = [1 zeros(1,100)];
587. y3 = [0 0];
588. for i = 1:length(x3)
589. n3 = i+2;
590. y3(n3) = (A*x3(i) + (-1*C*y3(n3-1))) +(B*x3(i) + D*y3(n3-1));
591. end
592. y3 = y3(3:n3);
593.
594. figure(3)
595. subplot(3,1,1)
596. stem(y3)
597. title('Respon Impulse sistem')
598.
599. subplot(3,1,2)
600. m3 = 100; %jumlah sample
601. BB3 = [1 0 0]; %numerator
602. AA3 = [A-B -C-D 0]; %denominator
603. impz(BB3,AA3,m3)
604.
605. [Z3,P3,K3] = tf2zp(BB3,AA3)
606.
607. subplot(3,1,3)
608. zplane(BB3,AA3)
609.
610.
611. %4.
612. x4 = [1 zeros(1,100)];
613. y4 = [0 0];
614. for i = 1:length(x4)
615. n4 = i+2;
616. y4(n4) = exp(x4(i)) + (-1*A*y4(n4-1)) + (-1*B*y4(n4-2)) + (C*y4(n4-1)) + (D*y4(n4-2));
617. end
618. y4 = y4(3:n4);
619.
620. figure(4)
621. subplot(3,1,1)
622. stem(y4)
623. title('Respon Impulse sistem')
624.
625. subplot(3,1,2)
626. m4 = 100; %jumlah sample
627. BB4 = [1 0 0]; %numerator
628. AA4 = [exp(1) -A+C -B+D]; %denominator
629. impz(BB4,AA4,m4)
630.
631. [Z4,P4,K4] = tf2zp(BB4,AA4)
632.
633. subplot(3,1,3)
634. zplane(BB4,AA4)
RAW Paste Data
We use cookies for various purposes including analytics. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy.

Top