  The paper investigates uniform convergence of wavelet expansions of Gaussian
random processes. The convergence is obtained under simple general conditions
on processes and wavelets which can be easily verified. Applications of the
developed technique are shown for several classes of stochastic processes. In
particular, the main theorem is adjusted to the fractional Brownian motion
case. New results on the rate of convergence of the wavelet expansions in the
space $C([0,T])$ are also presented.
