  We have studied the averaged power density spectra (PDSs) of two classes of
long-duration gamma-ray bursts in the recent classification by Balastegui et
al.(2001) based on neural network analysis. Both PDSs follow a power law over a
wide frequency range with approximately the same slope, which indicates that a
process with a self-similar temporal property may underlie the emission
mechanisms of both. The two classes of bursts are divided into groups according
to their brightness and spectral hardness respectively and each group's PDS was
calculated; For both classes, the PDS is found to flatten both with increasing
burst brightness and with increasing hardness.
