Generating model noise

Generating non-white random noise means producing arbitrary long time series with a given spectral density. Such time series are needed for example for the following purposes:

One way of doing this is to apply digital filters (FIR or IIR) to white input noise.
This approach is effectively implemented for the generation of multichannel noise with a given cross spectral density.
Multichannel transfer functions are identified by an automatic fit procedure based on a modified version of the vector-fitting algorithm (see Z-Domain Fit for further details on the algorithm).
Partial fraction expansion of multichannel transfer functions and the implementation of filter state initialization avoid the presence of unwanted 'warm-up period'.

A different approach is implemented in LTPDA as Franklin noise-generator.
It produces spectral densities according to a given pole zero model (see Pole/Zero Modeling) and does not require any warm-up period.

©LTP Team