A generalization of projection pursuit for time series, that is, signals wi
th time structure, is introduced. The goal is to find projections of time s
eries that have interesting structure, defined using criteria related to Ko
lmogoroff complexity or coding length. Interesting signals are those that c
an be coded with a short code length. We derive a simple approximation of c
oding length that takes into account both the nongaussianity and the autoco
rrelations of the time series. Also, we derive a simple algorithm for its a
pproximative optimization. The resulting method is closely related to blind
separation of nongaussian, time-dependent source signals.