Adding noise to a Gaussian

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Nicole Bonino
Nicole Bonino 2015-8-8
评论： Image Analyst 2015-8-9
My code keeps returning an error saying my signal-to-noise ratio must be a real scalar.
this is my code:
y=A.*exp((-(x-x_0).^2)./s);
% part a
A=100;
x=[-0.5:.01:.5-.01];
x_0=0;
s=1;
figure(2)
G=Gaussian(A,x,x_0,s);
plot(x,G)
% part b
n = rand(1,100);
Gnew1= y + 0*n;
Gnew2= y + 0.5*n;
Gnew3= y + 7.5*n;
Gnew4= y + 15*n;
figure(3)
w = awgn(x,n);
plot(x,G,x,w)
legend('Original Gaussian','Gaussian with Noise');
plot(x, Gnew1)
hold on
plot(x, Gnew2)
plot(x, Gnew3)
plot(x, Gnew4)
hold off
Here is the problem:
This problem deals with data fitting in the presence of noise.
a. Write a function Gaussian.m which will generate a 1D Gaussian function of the form y=A.*exp((-(x-x_0).^2)./s);, where s is the spread of the Gaussian, A is a constant factor and the mean x_0. The inputs to the function should be a vector of values (x), A, , and !. To test your function, plot the Gaussian corresponding to x= [-0.5:0.01:0.5-0.01], A = 100, s = 1, and x0= 0.
b. Add noise the Gaussian you generated above and plot the corresponding result. You may use the randn.m function in Matlab to generate a 100 random (noise) values between 0-1. Hence the new Gaussian function (Gnew = y + factor*noise) can be obtained. On the same graph, plot out Gnew for 4 different values of factor = {0.0, 0.5, 7.5, 15}.
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Walter Roberson
Walter Roberson 2015-8-8
Please show the traceback of the error message. Which line is reporting that error?

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采纳的回答

Neo
Neo 2015-8-9
Does anyone know how to do part C for this problem?
C. Use the polyval and polyfit functions to fit polynomials of different degrees to the Gnew functions generated in (b) above. Fit 4 polynomials corresponding to degrees of 1, 2, 10, and 15 to Gnew for each value of factor (i.e. 0.0, 0.5, 7.5, 15). You should use the subplot function to generate 4 subplots on a single figure, each subplot corresponding to a different noise level.
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Walter Roberson
Walter Roberson 2015-8-9
noise = randn(size(y));
for Kb = 1 : nb
b = bvals(Kb);
Gnew{Kb} = y + b .* noise;
end
Image Analyst
Image Analyst 2015-8-9
Put that code into a function. Then just call the function for each of the 4 Gnew variables that you have.

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更多回答（1 个）

Walter Roberson
Walter Roberson 2015-8-8
http://www.mathworks.com/help/comm/ref/awgn.html
y = awgn(x,snr) adds white Gaussian noise to the vector signal x. The scalar snr specifies the signal-to-noise ratio per sample, in dB.
But your code has
n = rand(1,100);
w = awgn(x,n);
so the value you pass in for the second parameter is a vector 1 x 100, where the awgn routine needs a scalar.
  1 个评论
Image Analyst
Image Analyst 2015-8-8
Not to mention the fact that it said to use randn() - it didn't mention awgn(). Why do you want to use both? I'd use only the one noise addition function that you were told to use, and that is randn().

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