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What is FFT value?

Updated: 9/21/2023
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Q: What is FFT value?
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How do you plot frequency spectrum using fft function in MATLAB?

To plot the frequency spectrum using the fft function in MATLAB, first compute the one-dimensional discrete Fourier transform using fft, provide the data series as an input. Then use the abs() function to get the magnitude spectrum, and plot the result using the plot() function, with the frequency domain on the x-axis and the magnitude spectrum on the y-axis.


Matlab program for circular convolution using dft and idft?

clc clear all close all a = [1 2 3 4]; b = [6 7 8 9 10]; f=length(a); g=length(b); h=(f+g-1); i=[a,zeros(1,(h-f))]; j=[b,zeros(1,(h-g))]; y1 = fft(i); y2 = fft(j); z = y1.*y2; c = ifft(z); subplot(2,2,1); plot(a) title('a') subplot(2,2,2); plot(b) title('b') subplot(2,2,3); plot(c) title('Convolution of a,b')


What is the difference between a face value and a value in 3508?

The face value of 3 is 3: the value of 3 is 3000The face value of 5 is 5: the value of 5 is 500The face value of 3 is 3: the value of 3 is 3000The face value of 5 is 5: the value of 5 is 500The face value of 3 is 3: the value of 3 is 3000The face value of 5 is 5: the value of 5 is 500The face value of 3 is 3: the value of 3 is 3000The face value of 5 is 5: the value of 5 is 500


What if actual value - measured value is negative?

Then the measured value is larger than the actual value.


In mathematics what is a limiting value?

If the value of a function cannot be determined for any value of the independent variable, then, the value the function seems to be approaching would be its limiting value for that particular value of the independent variable.

Related questions

How do you plot FFT in simulink?

FFT is the frequency domain representation. In can be shown in Simulink with blocks. These blocks graphically show the domain or x value plotted against the frequency or y value.


How do you plot frequency spectrum using fft function in MATLAB?

To plot the frequency spectrum using the fft function in MATLAB, first compute the one-dimensional discrete Fourier transform using fft, provide the data series as an input. Then use the abs() function to get the magnitude spectrum, and plot the result using the plot() function, with the frequency domain on the x-axis and the magnitude spectrum on the y-axis.


What are there advantages and where are there used fft?

because they have a high speed compared to fft


What are there advantages and where are there used?

FFT reduces the computation since no. of complex multiplications required in FFT are N/2(log2N). FFT is used to compute discrete Fourier transform.


Need of fft?

FT is needed for spectrum analysis, FFT is fast FT meaning it is used to obtain spectrum of a signal quickly, the FFT algorithm inherently is fast algorithm than the conventional FT algorithm


What is the need of FFT?

There's no need for it.


Why FFT is faster than DFT?

FFT is faster than DFT because no. of complex multiplication in DFT is N^2 while in FFT no. of complex multiplications are N/2(log2N). for example if N=8 no. of complex multiplications required in DFT are 64. while no. of complex multiplications required in FFT are 12 thus reduces computation time.


What does fft mean in txt talk?

Food For Thought


What is the meaning of fft in ofdma?

Fast Fourier Transform


C coding for cooley tukey fft algorithm?

hi.... for DIT fft algorithm, refer to this link, it has c-code for that. http://cnx.org/content/m12016/latest/


How much health does wiegraf have in demon form on fft?

1045


Difference between the DFT and the FFt?

A Discrete Fourier Transform is simply the name given to the Fourier Transform when it is applied to digital (discrete) rather than an analog (continuous) signal. An FFT (Fast Fourier Transform) is a faster version of the DFT that can be applied when the number of samples in the signal is a power of two. An FFT computation takes approximately N * log2(N) operations, whereas a DFT takes approximately N^2 operations, so the FFT is significantly faster simple answer is FFT = Fast DFT