Understanding the result of the fft algorithm.
I need help understanding the FFT calculation results.
Recently, I have been interested in signal analysis, so I have created and understood fft algorithms.
My specific questions are as follows.
When the complex number, which is the result of the fft transformation, is displayed on the complex plane and the distance from the origin is calculated, the meaning of the value is known as amplitude. The result of the fft algorithm is complex, and the absolute value of the real part is less than 10, and the absolute value of the imaginary part is more than 10000. Is this the right situation? Currently, the length of the voice signal data is 41278.
Below is part of the result value.
{ re: 12.010356845500022, im: 6790.977397750974 }
{ re: 11.331472604179078, im: 3384.867732243245 }
{ re: 10.868698153019578, im: 3968.6697612994003 }
{ re: 10.930208906879702, im: 1689.332725124391 }
{ re: 8.25000967783374, im: 12436.209080582033 }
{ re: 10.189814004377867, im: 1982.4643461369433 }
{ re: 10.71733497571107, im: 6623.352885444263 }
{ re: 9.554291319475688, im: 862.3145173349678 }
{ re: 7.35670677360367, im: 11270.160881373446 }
{ re: 7.571125714550484, im: 6202.489135470153 }
[Additional explanation]
My question is simple. I wonder if the fft algorithm made of nodejs worked normally.
The signal data length is 41278, The frequency range was set to 2^16, a value of 2^n greater than the signal data length.
0 ~ 41278 : signal data
41279 ~ 2^16 : signal data = 0
length : 2^16 = 65536
The result of performing the fft conversion in this state... While the number of real numbers is small, The imaginary part is very big. I wonder if the fft transformation is correct.
If the fft conversion result is calculated as the distance from the origin of the complex plane, the amplitude of the corresponding frequency comes out, and my result is that the amplitude is too large.