Synthesis of the nonlinear parametric identification algorithm based on the minimum criterion of the estimation error probability

The paper demonstrates the topicality of alternative (with respect to conventional) techniques for stochastic nonlinear parametric identification. The identification procedure of the discrete observer parameter based on the minimum criterion of the estimation error probability is offered herein for the first time. A model example that demonstrates the efficiency of the technique proposed is considered. The algorithm based on the generalized probabilistic criterion can be used in a vast variety of applications in the fields of communication, control, metrology, etc.