Is signal reconstruction possible using phase/magnitude only

AI Thread Summary
Reconstructing a signal using only its phase or magnitude is a complex topic in Fourier Transform studies. While both components are typically needed for accurate reconstruction, it is possible to approximate a signal using just the magnitude by applying the Hilbert transform to derive the imaginary part. The ear may not perceive phase differences in certain contexts, such as with constant amplitude sounds, but phase plays a crucial role in distinguishing between closely spaced frequencies. For example, two waves at 440 Hz and 441 Hz can create a perceptible amplitude modulation, highlighting the importance of phase in sound perception. Overall, while minimal phase reconstruction techniques exist, the complete fidelity of a signal generally requires both phase and magnitude.
ramdas
Messages
78
Reaction score
0
I am studying Fourier Transform and it's inverse. We get phase and magnitude of a signal from it's Fourier transform and reconstruct it back from both together(magnitude of signal +phase of signal)

My question is that is it possible to reconstruct given signal back using it's phase only or magnitude only?
 
Mathematics news on Phys.org
ramdas said:
I am studying Fourier Transform and it's inverse. We get phase and magnitude of a signal from it's Fourier transform and reconstruct it back from both together(magnitude of signal +phase of signal)

My question is that is it possible to reconstruct given signal back using it's phase only or magnitude only?
For a complex waveform, we would need to add each component in its correct amplitude and phase in order to obtain the correct shape. But for sound, the ear does not seem to notice the phase, so the shape of the wave is not important provided the spectral response is correct.
 
There is such a notion as a minimal phase reconstruction in signal processing. Here's an outline of the process:
Suppose you have an analytic signal:
x(t)=A(t)eiφ(t)

Then (a) log of the signal would be:
log(x(t)) = log(|A(t)|)+iφ(t)

Now, what if we just have A(t)?
You can take log(|A(t)|) and call it the real part of an analytic signal, but what about the imaginary part?
It turns out you can take what is called the Hilbert transform of log(|A(t)|) to get a good candidate for the missing imaginary part. Add the real and imaginary parts, then exponentiate to get your reconstruction.

If you have access to MATLAB, you can try this out using the built in 'hilbert' function. If you pass it a time series, it uses the Fast Fourier Transform to make an analytic signal.
 
tech99 said:
For a complex waveform, we would need to add each component in its correct amplitude and phase in order to obtain the correct shape. But for sound, the ear does not seem to notice the phase, so the shape of the wave is not important provided the spectral response is correct.
That is true for short timescales (e.g. if you want to describe a single note played by an instrument at constant amplitude) but it is not true in general.
Consider a 440 Hz wave and a 441 Hz wave at the same amplitude together: a human will interpret this as ~440 Hz sound that oscillates in amplitude once per second. The question "when do we hear sound?" depends on the phases of the two waves.
 
Suppose ,instead of the usual x,y coordinate system with an I basis vector along the x -axis and a corresponding j basis vector along the y-axis we instead have a different pair of basis vectors ,call them e and f along their respective axes. I have seen that this is an important subject in maths My question is what physical applications does such a model apply to? I am asking here because I have devoted quite a lot of time in the past to understanding convectors and the dual...
Insights auto threads is broken atm, so I'm manually creating these for new Insight articles. In Dirac’s Principles of Quantum Mechanics published in 1930 he introduced a “convenient notation” he referred to as a “delta function” which he treated as a continuum analog to the discrete Kronecker delta. The Kronecker delta is simply the indexed components of the identity operator in matrix algebra Source: https://www.physicsforums.com/insights/what-exactly-is-diracs-delta-function/ by...

Similar threads

Back
Top