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Exercise: Use MATLAB to generate the sinusoidal waveform: x(t) = 3 cos(1200) Consider...
need matlab code Exercise: Use MATLAB to generate a low frequency signal: xy(t) = 3 cos(1400)...
need matlab code
Exercise: Use MATLAB to generate a low frequency signal: xy(t) = 3 cos(1400) And a higher frequency signal: xz(t) = 2 cos(10,000st) Now add these two signals together to generate the dual-component signal: y(t) = 3 cos(14007a)+ 2 cos(10,000) Points to be addressed: Again, manually calculate the theoretical magnitude spectra of y(t) and show this in your report (use Microsoft Visio or similar for your diagram). Clearly label all axes! Contrast this working to what you see...
Write a Matlab code to generate the signal y(t)=10*(cos(2*pi*f1*t)+ cos(2*pi*f2*t)+ cos(2*pi*f3*t)), where f1=500 Hz, f2=750 Hz...
Write a Matlab code to generate the signal y(t)=10*(cos(2*pi*f1*t)+ cos(2*pi*f2*t)+ cos(2*pi*f3*t)), where f1=500 Hz, f2=750 Hz and f3=1000 Hz. Plot the signal in time domain. Sketch the Fourier transform of the signal with appropriately generating frequency axis. Apply an appropriate filter to y(t) so that signal part with frequency f1 can be extracted. Sketch the Fourier transform of the extracted signal. Apply an appropriate filter to y(t) so that signal part with frequency f2 can be extracted. Sketch the Fourier...
Now use MATLAB to generate and plot 15seconds of this signal in the time-domain.Use the fft()...
Now use MATLAB to generate and plot 15seconds of this signal
in the time-domain.Use the fft() function to find the fourier
transform of this signal and plot its magnitude spectrum
School of Engineering Task 3 - The Fourier Transform: Scaling property Exercise: Let's take a look now at using the Fourier transform on aperiodic signals. Consider the real exponential signal from the discharging capacitor in tas 3 of laboratory 1 which was found to be: You(t)=e"u(t) Begin by calculating manually...
3) Given three sinusoids with the following amplitude and phases (t)-Scos(2x (1200+0.25x) a. Create a MATLAB...
3) Given three sinusoids with the following amplitude and phases (t)-Scos(2x (1200+0.25x) a. Create a MATLAB program to sample each sinusoid and generate a sum of three sinusoids, that is, х(n)=x1(nHx:(n)+xy(n), using a sampling rate of 8000 Hz, and plot the sum x(n) over a range of time that will exhibit approximately 0.1 second. (10 pts) b. Use the MATLAB function fO to compute DFT coefficients, and plot and examine the spectrum of the signal x(n).(10 pts Write a MATLAB...
3) Given three sinusoids with the following amplitude and phases (t)-Scos(2x (1200+0.25x) a. Crea...
3) Given three sinusoids with the following amplitude and phases (t)-Scos(2x (1200+0.25x) a. Create a MATLAB program to sample each sinusoid and generate a sum of three sinusoids, that is, х(n)=x1(nHx:(n)+xy(n), using a sampling rate of 8000 Hz, and plot the sum x(n) over a range of time that will exhibit approximately 0.1 second. (10 pts) b. Use the MATLAB function fO to compute DFT coefficients, and plot and examine the spectrum of the signal x(n).(10 pts Write a MATLAB...
Exercise 4. Computing and displaying the Fourier Transform of a signal Later in the semester it will become useful to d...
Exercise 4. Computing and displaying the Fourier Transform of a signal Later in the semester it will become useful to determine the frequency response of a signal or system by taking the Fourier Transform empirically (rather than computing it analytically). To do so we make use of the fft and fftshift commands. The fft command is an efficient implementation of the Discrete Fourier Transform (DFT) known as the Fast Fourier Transform (FFT). When the FFT is computed the samples are...
(A.) Use MATLAB to generate a pulsed sine wave signal having a frequency F-10KHZ and a...
(A.) Use MATLAB to generate a pulsed sine wave signal having a frequency F-10KHZ and a pulse width of T-.5ms. The pulse repetition time is 1ms (pulse repetition rate is 1000 pulses/sec), i.e., the signal is zero between pulses. Model the signal to start at time t-0 and to end at a time t=Tstop. Use a sample time of .001ms to approximate an analog environment. Display the signal in MATLAB appropriate for an analog signal, first for Tstop 1ms and...
Exercises: u used to the instructor b the end of next lab. 20 102 Plot the f(t)-sinc(20r) cos(300...
Exercises: u used to the instructor b the end of next lab. 20 102 Plot the f(t)-sinc(20r) cos(300t)sinc (10t) cos(100t) Use the fast Fourier transform to find the magnitude and phase spectrum of the signal and plot over an appropriate range. Use appropriate values for the time interval and the sampling interval. Note that in Matlab sinc(x)-, so we need to divide the argument by n to make it match the given function. Le, sinc(20t/pi) Hint: Use the parameters from...
Can you please help me answer Task 2.b? Please show all work. fs=44100; no_pts=8192; t=([0:no_pts-1]')/fs; y1=sin(2...
Can you please help me answer Task 2.b?
Please show all work.
fs=44100; no_pts=8192;
t=([0:no_pts-1]')/fs;
y1=sin(2*pi*1000*t);
figure;
plot(t,y1);
xlabel('t (second)')
ylabel('y(t)')
axis([0,.004,-1.2,1.2]) % constrain axis so you can actually see
the wave
sound(y1,fs); % play sound using windows driver.
%%
% Check the frequency domain signal. fr is the frequency vector and
f1 is the magnitude of F{y1}.
fr=([0:no_pts-1]')/no_pts*fs; %in Hz
fr=fr(1:no_pts/2); % single-sided spectrum
f1=abs(fft(y1)); % compute fft
f1=f1(1:no_pts/2)/fs;
%%
% F is the continuous time Fourier. (See derivation...
consider the signal using matlab Problem 2: Consider a signal: x[n] 3cos(n7/3) + 2sin(nt/4)+ cos(n7/5) Using...
consider the signal using matlab
Problem 2: Consider a signal: x[n] 3cos(n7/3) + 2sin(nt/4)+ cos(n7/5) Using Matlab, (1) Plot this signal in time domain. Can you identify the various frequencies in this signal? Use n 0:1:1000 (2) Plot this signal in frequency domain using the "fft" command. Identify the individual frequencies in the plot. (3) Calculate the frequencies of these signals. In the frequency plot, 1000 2
need matlab code
Exercise: Use MATLAB to generate a low frequency signal: xy(t) = 3 cos(1400) And a higher frequency signal: xz(t) = 2 cos(10,000st) Now add these two signals together to generate the dual-component signal: y(t) = 3 cos(14007a)+ 2 cos(10,000) Points to be addressed: Again, manually calculate the theoretical magnitude spectra of y(t) and show this in your report (use Microsoft Visio or similar for your diagram). Clearly label all axes! Contrast this working to what you see...
Now use MATLAB to generate and plot 15seconds of this signal
in the time-domain.Use the fft() function to find the fourier
transform of this signal and plot its magnitude spectrum
School of Engineering Task 3 - The Fourier Transform: Scaling property Exercise: Let's take a look now at using the Fourier transform on aperiodic signals. Consider the real exponential signal from the discharging capacitor in tas 3 of laboratory 1 which was found to be: You(t)=e"u(t) Begin by calculating manually...
3) Given three sinusoids with the following amplitude and phases (t)-Scos(2x (1200+0.25x) a. Create a MATLAB program to sample each sinusoid and generate a sum of three sinusoids, that is, х(n)=x1(nHx:(n)+xy(n), using a sampling rate of 8000 Hz, and plot the sum x(n) over a range of time that will exhibit approximately 0.1 second. (10 pts) b. Use the MATLAB function fO to compute DFT coefficients, and plot and examine the spectrum of the signal x(n).(10 pts Write a MATLAB...
3) Given three sinusoids with the following amplitude and phases (t)-Scos(2x (1200+0.25x) a. Create a MATLAB program to sample each sinusoid and generate a sum of three sinusoids, that is, х(n)=x1(nHx:(n)+xy(n), using a sampling rate of 8000 Hz, and plot the sum x(n) over a range of time that will exhibit approximately 0.1 second. (10 pts) b. Use the MATLAB function fO to compute DFT coefficients, and plot and examine the spectrum of the signal x(n).(10 pts Write a MATLAB...
Exercise 4. Computing and displaying the Fourier Transform of a signal Later in the semester it will become useful to determine the frequency response of a signal or system by taking the Fourier Transform empirically (rather than computing it analytically). To do so we make use of the fft and fftshift commands. The fft command is an efficient implementation of the Discrete Fourier Transform (DFT) known as the Fast Fourier Transform (FFT). When the FFT is computed the samples are...
(A.) Use MATLAB to generate a pulsed sine wave signal having a frequency F-10KHZ and a pulse width of T-.5ms. The pulse repetition time is 1ms (pulse repetition rate is 1000 pulses/sec), i.e., the signal is zero between pulses. Model the signal to start at time t-0 and to end at a time t=Tstop. Use a sample time of .001ms to approximate an analog environment. Display the signal in MATLAB appropriate for an analog signal, first for Tstop 1ms and...
Exercises: u used to the instructor b the end of next lab. 20 102 Plot the f(t)-sinc(20r) cos(300t)sinc (10t) cos(100t) Use the fast Fourier transform to find the magnitude and phase spectrum of the signal and plot over an appropriate range. Use appropriate values for the time interval and the sampling interval. Note that in Matlab sinc(x)-, so we need to divide the argument by n to make it match the given function. Le, sinc(20t/pi) Hint: Use the parameters from...
Can you please help me answer Task 2.b?
Please show all work.
fs=44100; no_pts=8192;
t=([0:no_pts-1]')/fs;
y1=sin(2*pi*1000*t);
figure;
plot(t,y1);
xlabel('t (second)')
ylabel('y(t)')
axis([0,.004,-1.2,1.2]) % constrain axis so you can actually see
the wave
sound(y1,fs); % play sound using windows driver.
%%
% Check the frequency domain signal. fr is the frequency vector and
f1 is the magnitude of F{y1}.
fr=([0:no_pts-1]')/no_pts*fs; %in Hz
fr=fr(1:no_pts/2); % single-sided spectrum
f1=abs(fft(y1)); % compute fft
f1=f1(1:no_pts/2)/fs;
%%
% F is the continuous time Fourier. (See derivation...
consider the signal using matlab
Problem 2: Consider a signal: x[n] 3cos(n7/3) + 2sin(nt/4)+ cos(n7/5) Using Matlab, (1) Plot this signal in time domain. Can you identify the various frequencies in this signal? Use n 0:1:1000 (2) Plot this signal in frequency domain using the "fft" command. Identify the individual frequencies in the plot. (3) Calculate the frequencies of these signals. In the frequency plot, 1000 2
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