1 (Original periodic signal 1) - Sawtooth wave T = 50*(1/50); dx = 0.0001; fs =...

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1 (Original periodic signal 1) - Sawtooth wave T = 50*(1/50); dx = 0.0001; fs = 1/dx; t = 0:1/fs:T-1/fs; [aaa bbb] = size(t); Periodic = 10; x = sawtooth(2* pi* Periodic *t); figure plot(t,x, 'linewidth',3) grid on axis ([0 1-1 1]); 0.8- 0.6 0.4 0.2 OF -0.2 -0.4- -0.6 -0.8 0 0.01 0.02 0.03 0.04 0.06 0.06 0.07 0.08 0.09 0.1 g2 (Original periodic signal 2) Periodic pulse dx = 0.0001; freq=10/200; offset=0; amp=2; duty=50; t=0:dx:100; %100 seconds [aaa bbb] = size(t); x=offset+amp*square (2*pi*freq. *t,duty); figure plot(t,x, 'linewidth",2) grid on 7/13 I 100% 1.5 1 0.5 0 -0.5 -1 -1.5 -2 0 H 20 40 60 80 100 8/13 100% + You have to obtain the following results for the above two signals (square and sawtooth signals) (i) Amplitude plot of the Fourier coefficient (use "stem" in MATLAB) (ii) Angle plot of the Fourier coefficient (use "stem" in MATLAB) (iii) The plot of the approximated signals via the Fourier series when N = 10 and N= 100 in (1). In this plot, you also have to plot the original signal r, and compare the original signal with the approximated signal obtained from (1) when N= 10 and N = 100. You can use "integral" in MATLAB to compute the Fourier coefficient 1 (Original periodic signal 1) - Sawtooth wave T = 50*(1/50); dx = 0.0001; fs = 1/dx; t = 0:1/fs:T-1/fs; [aaa bbb] = size(t); Periodic = 10; x = sawtooth(2* pi* Periodic *t); figure plot(t,x, 'linewidth',3) grid on axis ([0 1-1 1]); 0.8- 0.6 0.4 0.2 OF -0.2 -0.4- -0.6 -0.8 0 0.01 0.02 0.03 0.04 0.06 0.06 0.07 0.08 0.09 0.1 g2 (Original periodic signal 2) Periodic pulse dx = 0.0001; freq=10/200; offset=0; amp=2; duty=50; t=0:dx:100; %100 seconds [aaa bbb] = size(t); x=offset+amp*square (2*pi*freq. *t,duty); figure plot(t,x, 'linewidth",2) grid on 7/13 I 100% 1.5 1 0.5 0 -0.5 -1 -1.5 -2 0 H 20 40 60 80 100 8/13 100% + You have to obtain the following results for the above two signals (square and sawtooth signals) (i) Amplitude plot of the Fourier coefficient (use "stem" in MATLAB) (ii) Angle plot of the Fourier coefficient (use "stem" in MATLAB) (iii) The plot of the approximated signals via the Fourier series when N = 10 and N= 100 in (1). In this plot, you also have to plot the original signal r, and compare the original signal with the approximated signal obtained from (1) when N= 10 and N = 100. You can use "integral" in MATLAB to compute the Fourier coefficient

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The MATLAB code for obtaining the results for the square and sawtooth signals as requested matlab Fourier Series Approximation Functions function a fo... View the full answer