The paper presents the intelligent information technology to increase the efficiency of
diagnosing the state of nonlinear dynamical objects of different physical nature with the use of
mathematical models in the form of Volterra kernels. Research results on the test object
monitoring show that moments of nuclei Volterra 2nd order characterized by the highest stability
of the quality of diagnosis (probability of correct recognition) errors in measuring the response of
objects of control compared to the data of their classification on the basis of samples of nuclei with
a given increment.
