Complex signal sine reconstruction Noob here, I read that any signal can be made by putting together sines and cosines, it always shows some kind of basic harmonic wave with constant amplitude such as square wave.

I understand that constant amplitude, constant frequency square and triangle waves can be made from sines, but what about square wave that sweeps its frequency or even suddenly jump to other frequency, what about square that has its amplitude changed?

What about noise, lets say I have 1 minute long 48KHz 16bit PCM signal that is just white noise, that can be reconstructed from bunch of sines too?

And what about transients, either the sudden square wave like ones or the gentle slow fade in type ones. Lets say I have signal that is silence and then square wave slowly and smoothly rises in amplitude, how can sines, which are constant in amplitude ever recreate it?

Basically, my point is these sines are constant in amplitude, frequency, and phase and they run the entire lenght of whatever signal we want to reconstruct, signals can have silence, transients, periods where amplitude and frequency is constant and periods where they change. I dont understand how can bunch of sines that run the entire lenght of complex signal ever reconstruct it. How can 1000 sine waves sum up into perfect silence and then suddenly sum into noisy square wave sweep?
A sum of sines/cosines (with frequencies that are integer multiples of a fundamental frequency) will always result in a periodic function (that's what Fourier series are about). But you can of course approximate any function with finite support by choosing the length of the function's support as your period (if you don't mind that the approximation will be a periodic continuation of the given function).

Note that the approximation by a Fourier series is a least squares approximation, not a point-wise approximation. So if the desired function has discontinuities there will always remain some error of fixed magnitude, no matter how many sinusoids you use for the approximation. This oscillatory behavior near discontinuities is called Gibbs phenomenon.