- #1

- 3,238

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I tried using fft but I can't get it to work.

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- MATLAB
- Thread starter Cyrus
- Start date

In summary, the function easyspec allows for easy spectral analysis in MATLAB and can also plot the spectrum and return the results. It uses a hanning window and zero-padding for smooth results. The frequency domain goes from DC to the Nyquist frequency and the function uses random sample segments for calculation.

- #1

- 3,238

- 16

I tried using fft but I can't get it to work.

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- #2

- 3,238

- 16

Code:

```
function [s,f]=easyspec(x,fs)
%EASYSPEC Easy plot of spectrum estimate
% S=EASYSPEC(X) will return a spectrum vector of
% X. [S,F]=EASYSPEC(X,FS) will also return a freuqency
% axis in F, while the sample frequency is given in FS.
% EASYSPEC(X) and EASYSPEC(X,FS), will plot the spectrum
% and return the S vector in MATLAB's "ans".
% Notes:
% 1. Spectrum values are in dB.
% 2. The frequency domain goes from DC to the Nyquist
% frequency. The "mirror part" of the spectrum is
% omitted.
% 3. The sample segments, from which the spectrum is
% calculated are picked by random. The function might
% return significantly different results each time it's
% called to if X isn't stationary.
% 4. EASYSPEC uses a hanning window and zero-pads by a
% factor of 4. The spectrum vector will look smooth.
% Eli Billauer, 17.1.01 (Explicitly not copyrighted).
% This function is released to the public domain; Any use is allowed.
if nargin==0
error('No input vector given');
end
if (nargin==1)
fs=2;
end
NFFT=16384; NWIN=NFFT/4;
LOOP=100;
win=hanning(NWIN)';
x=x(:)'*(17.127/NFFT/sqrt(LOOP));
n=length(x);
maxshift=n-NWIN;
if (n<2*NWIN)
error(['Input vector should be at least of length '...
num2str(2*NWIN)]);
end
s=zeros(1,NFFT);
for i=1:LOOP
zuz=floor(rand*maxshift);
s=s+abs(fft([win.*x(1+zuz:NWIN+zuz) zeros(1,NFFT-NWIN)])).^2;
end
s=10*log10(s(1:NFFT/2));
f=linspace(0,fs/2,NFFT/2);
if nargout==0
hold off;
plot(f,s);
ylabel('Power Spectrum [dB]');
xlabel('Frequency');
grid on; zoom on;
end
```

- #3

- 2,892

- 0

Sure, I'd be happy to help with your spectral analysis code in MATLAB. Can you provide more information about the curve you are trying to analyze and what specific issue you are having with the fft function? That will help me provide you with a more tailored solution. In the meantime, here is a general outline for performing spectral analysis in MATLAB using the fft function:

1. First, make sure your data is in a vector format. If it is in a matrix format, you can use the "reshape" function to convert it into a vector.

2. Next, use the fft function to compute the fast Fourier transform of your data. This will give you a complex-valued vector.

3. To plot the spectrum, you can use the "abs" function to get the magnitude of the complex values and then plot them against the corresponding frequency values using the "plot" function.

4. If you want to see the spectrum in decibels, you can use the "20*log10" function to convert the magnitude values.

5. You can also use the "fftshift" function to shift the zero-frequency component to the center of the spectrum for better visualization.

6. Finally, you can use the "xlabel" and "ylabel" functions to label your plot with the appropriate frequency and magnitude units.

I hope this helps get you started with your spectral analysis in MATLAB. If you have any specific questions or issues, please feel free to provide more details and I will do my best to assist you further.

MATLAB Spectral Analysis Code is a set of functions and algorithms designed to analyze and manipulate spectral data in the MATLAB programming environment.

To use MATLAB Spectral Analysis Code, you must have the MATLAB software installed on your computer. Once installed, you can access the code through the MATLAB command window or by writing scripts and functions in the MATLAB programming language.

MATLAB Spectral Analysis Code can be used to analyze a wide range of spectral data, including signals, images, and multidimensional data. It is commonly used in fields such as signal processing, image analysis, and data science.

To effectively use MATLAB Spectral Analysis Code, you should have a basic understanding of the MATLAB programming language and its syntax. Prior knowledge of signal processing and spectral analysis concepts can also be helpful.

Yes, MATLAB Spectral Analysis Code is highly customizable and can be adapted to fit your specific needs and data. You can modify existing functions or create your own functions to perform specific spectral analysis tasks.

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