Fourier Analysis: Signal Representation & Non-Monochromatic Light/Sound

AI Thread Summary
Fourier Analysis is a mathematical tool that allows for the representation of periodic signals as a sum of sine waves. It can be applied to various physical phenomena, including non-monochromatic light sources and sound waves, breaking them down into their constituent frequencies. The technique is versatile and can also be utilized in non-periodic functions through Fourier transforms. Applications extend beyond classical physics to areas like quantum physics, where it is used to analyze probability waves. Overall, Fourier Analysis is essential for understanding complex signals across multiple fields.
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From what I understand, I can use Fourier Analysis to represent a periodic signal using a sum of sine waves. However, isn't this just a mathematical tool? Can I take any non-monochromatic light source and use Fourier Analysis to break it into a sum of the physically meaningfuly frequencies it's made of up? What about for sound?
 
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cscott said:
From what I understand, I can use Fourier Analysis to represent a periodic signal using a sum of sine waves. However, isn't this just a mathematical tool? Can I take any non-monochromatic light source and use Fourier Analysis to break it into a sum of the physically meaningfuly frequencies it's made of up? What about for sound?
It is a mathematical tool that can be applied to any function (that is physically reasonanble..there are some restrictions which are almost never of concern in physical applications) ...and if you include Fourier transforms, the function does not even have to be periodic.

Of course it can be applied to sound waves, electromagnetic waves, electric signals, the beating of a heart, and on and on. It is even applied to the probability waves of quantum physics.
 
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