Some signals can be conveniently written as a product of a slowly-varying amplitude function and a rapidly-varying sinusoid or sum of sinusoids. Let a signal have amplitude function a(t) = 3(t^0.5)(10^(−t)) and sum of sinusiods c(t) = 0.5 sin(2 π 300 t) + 0.5 sin(2 π 450 t). Multiply these to obtain the total signal, y(t) = a(t) c(t). Let the time interval be from 0 to 5 seconds and the sample rate be 8000 samples per second. Plot a(t) vs. t over the entire time interval. Plot c(t) vs. t but show only about a 0.03 second interval on the time axis so the waveform is clearly visible. Use the "sound" function to play the sound and describe what you hear. MATLAB CODE NEEDED!!!!!!!!!!!!!!!!!

clear all
close all
%initialzing time vector from 0 to 5 sec with 8000 samples per
second
t=0:1/8000:5;
%defining a(t)
a=3*sqrt(t).*10.^(-t);
%defining c(t)
c=0.5*sin(2*pi*300*t)+0.5*sin(2*pi*450*t);
%obtaining y(t)=a(t)*c(t)
y=a.*c;
%plotting a(t) vs. t for full time 0 to 5 seconds
figure(1)
plot(t,a,'LineWidth',1.5);
xlabel('Time (sec)')
ylabel('a(t)')
legend({'a(t)=3t^{0.5}10^{-t}'},'Box','off')
%plotting c(t) vs. t for first 0.03 seconds
figure(2)
plot(t(t<=0.03),c(t<=0.03),'LineWidth',1.5)
xlabel('Time (sec)')
ylabel('c(t)')
legend({'c(t)=0.5sin(2\pi300t)+0.5sin(2\pi450t)'},'Box','off')
%using the sound function to play y(t)
sound(y)


Some signals can be conveniently written as a product of a slowly-varying amplitude function and ...
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...
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LMS project Using the notes discussed in class: Implementing the LMS Algorithm First generate some signals clear all close al1: Generate signals for testing the LMS Algorithm 1000 Fs Sampling frequency Sample time 1/Fs 10000: = L Length of signal S Time vector (0:L-1) *T ; Sum of a 50 Hz sinusoid and a 120 Hz sinusoid 0.7 sin (2*pi*50*t); inuside X d+ 10 randn (size (t)); Sinusoids 5O0000000L plus noise fiqure (1) plot (Fs*t (1:150),x (1:1500)) title('Signal Corrupted with...
Generate plots for the function in Example 8.1 with sample intervals of 0.5 sec, 1 sec, and 10 sec. Explain the results in light of the sampling theorem. Example 8.1 Sampling Theorem and Aliasing Consider the function FO sin( at)+sin br) Using a trigonometric identity for the sum of two sinusoidal functions, we can rewrite FO as the following product: a+ b If frequencies a and b are close in value, the bracketed term has a very low frequency in...
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...
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Please offer the Matlab code.Answer the question b.c.f.g.
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