“…Most of popular adaptation algorithms need information about dependence of cost function on weights changes (it is often represented by the Jacobian matrix with first-order partial derivatives) [2]. The exact level presenting the influence of several weights on output error is obtained mostly using propagation of the error through neural network [3]. The second group of training algorithms based on the second order derivatives of the cost function according to weights (represented by Hessian matrix).…”