Solving FFT Signal Processing Problem for Complex Time Signal

AI Thread Summary
The discussion centers on a complex time signal x(t) and the challenges faced in retrieving the correct amplitudes X1 and X2 from its FFT representation. While the FFT successfully identifies the frequency components at ω and 2ω, the amplitudes do not match the expected values due to phase differences between the components. The user seeks guidance on how to accurately recover the amplitudes when multiple frequency components are present. Additionally, the importance of the sampling rate and the number of samples in relation to the frequency ω is highlighted as a crucial factor in the analysis. Proper execution of the FFT should yield the correct amplitudes if these parameters are adequately addressed.
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Hi, I have a complex time signal x(t)=X1*exp(i*∅)+X2*exp(i*2*∅). On converting to frequency domain, i expect frequency components at ω and twice of ω (when ∅=ω*t). FFT gives the desired frequencies, but the amplitudes don't correspond to X1 and X2. I understand that this is due to the phase difference between the signals X1*exp(i*∅1) and X2*exp(i*2*∅). My question is how should i get back the amplitudes X1,X2,... when multiple frequency components exist in the signal.

P.S: when only x(t)=X1*exp(i*∅1);am able to get back X1 in the fft.

Thanks in advance.
 
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It is not a question of phase. If you did everything correctly, you should get X1 and X2 back.

What is the sampling rate and number of samples compared to w?
 
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