FIELD: computer engineering.
SUBSTANCE: invention relates to the field of computer engineering and can be used for processing and prediction of values of data time series or continuous functional relationships. Device contains a unit of generating of a time series x(k), from the output of which via serially connected unit of complementary wavelet processing, unit of selecting approximation coefficients of m-th level Cm, as also the unit of formation of the sliding window of data from n counts of approximating coefficients using n-bit shift register, signals are given on inputs of the neural network built according to the scheme of multilayer perceptron of direct distribution, with the subsequent iterative teach procedure a neural network, during which is carried out setting of weight or synaptic coefficients based on the criterion of minimization of the prediction errors, generated in units of calculation of errors of the prediction e*r at all r outputs of neurons of an output layer of neural network, from the outputs of which approximation coefficients of prediction 
together with detail coefficients of wavelet expansion of time series di, obtained in the unit of their processing by smoothing algorithm based on the method of a penal threshold, come to inputs of units for recovery of output predicted values of function S(k + r), with the time of prediction for r periods of time series (r∈{1÷10}), at that the processed detail coefficients of expansion di together with approximation coefficients Cm are given to input of unit of the recovery of time series in real time S(k) with lowered error of representation of information due to its wavelet processing.
EFFECT: technical result is increase of prediction efficiency of changes of function values based on the criteria of duration and prediction error value, and also on high speed response of adaptability of the system under the changing conditions.
1 cl, 2 dwg, 1 tbl
