It is often assumed that the signals are usually stationary and linear
, perhaps, even Gaussian. In recent years attempts have been made to r
elax these assumptions. Here we attempt to review some techniques for
the analysis of such signals, and extend these techniques to deal with
signals which are both non-stationary and nonlinear.