  A functional method for calculating averages of the time-ordered exponential
of a continuous isotropic random $N\times N$ matrix process is presented. The
process is not assumed to be Gaussian. In particular, the Lyapunov exponents
and higher correlation functions of the T-exponent are derived from the
statistical properties of the process.
  The approach may be of use in a wide range of physical problems. For example,
in theory of turbulence the account of non-gaussian statistics is very
important since the non-Gaussian behavior is responsible for the time asymmetry
of the energy flow.
