> i'm having the following problem :

> i want to transform a stochastic signal (a PSD : two column vector, first one for frequency values, second for amplitude values) from Frequency domain to time domain using the "ifft", but i have no idea how to get the initial phases of the signal to do that. In fact the transformation in time domain has not a unique solution, it depends on initial conditions, is it right ?
> any idea how could i encounter this problem ?

> thanks

> > i'm having the following problem :

> > i want to transform a stochastic signal (a PSD : two column vector, first one for frequency values, second for amplitude values) from Frequency domain to time domain using the "ifft", but i have no idea how to get the initial phases of the signal to do that. In fact the transformation in time domain has not a unique solution, it depends on initial conditions, is it right ?
> > any idea how could i encounter this problem ?

> > thanks

> Since its stochastic, you can just use random phases.
> The 2nd order statistical properties (standard deviation and variance)
> will be preserved, no matter what the phases are.
> But before hitting it with ifft, you need to compose a vector of
> complex numbers.
> The composition of this vector depends upon what you have already.
> Does the frequency go from zero to the Nyquist, then negative?
> Or are all the frequencies positive?
> And is the first frequency zero?

> Basically, if Y is a column vector of complex numbers prepared from
> the amplitudes with the first frequency being greater than zero, then
> your vector for ifft should look like this:
> Y1=[0;Y;flipud(conj(Y))];
> If there is a zero frequency, it will look like this:
> Y1=[Y;flipud(conj(Y(2:end)))];