Add to ORKGThe task of nonparametric identification of dynamic objects with discrete-continuous nature of the process is conceded. The method of dynamic processes modeling, based on the nonparametric algorithms is offered. The complexity of dynamic process modeling under condition of incomplete information is discussed. The results of computing experiment explicitly are presented which show efficiency of this method, in case of simulation tasks solution
This article is dedicated to the models for different types of systems creation problem. Identificat...
Multivariable and closed-loop identification of large scale industrial processes is studied. The pro...
We propose a new probabilistic framework for nonparametric identification and estimation of dynamic ...
In this paper we consider the problem of modeling noninertial processes with stochastic dependence b...
AbstractThe analysis of existing methods of nonparametric identification of dynamic systems is shown...
System Identification is the art and science of building mathematical models of dynamical processes,...
The results of measurements of input-output variables of dynamical object are used for base for con...
Abstract. This paper establishes conditions for nonparametric identification of dynamic optimization...
AbstractThe problem of building a linear stationary model for a process given by evenly spaced discr...
AbstractThe problem of multialternative recognition of nonstationary random processes is considered....
The problem of nonlinear dynamical systems of Wiener type identification is considered. The parametr...
A method has been developed for identifying linear processes having one input and one output in the ...
The thesis deals with methods of identification of dynamic systems in time and frequency domain. Non...
In this paper we present a non-parametric approach to identification in networks. The main advantage...
Based on the analysis and systematization of the inverse problems of dynamics, the study of the prop...
This article is dedicated to the models for different types of systems creation problem. Identificat...
Multivariable and closed-loop identification of large scale industrial processes is studied. The pro...
We propose a new probabilistic framework for nonparametric identification and estimation of dynamic ...
In this paper we consider the problem of modeling noninertial processes with stochastic dependence b...
AbstractThe analysis of existing methods of nonparametric identification of dynamic systems is shown...
System Identification is the art and science of building mathematical models of dynamical processes,...
The results of measurements of input-output variables of dynamical object are used for base for con...
Abstract. This paper establishes conditions for nonparametric identification of dynamic optimization...
AbstractThe problem of building a linear stationary model for a process given by evenly spaced discr...
AbstractThe problem of multialternative recognition of nonstationary random processes is considered....
The problem of nonlinear dynamical systems of Wiener type identification is considered. The parametr...
A method has been developed for identifying linear processes having one input and one output in the ...
The thesis deals with methods of identification of dynamic systems in time and frequency domain. Non...
In this paper we present a non-parametric approach to identification in networks. The main advantage...
Based on the analysis and systematization of the inverse problems of dynamics, the study of the prop...
This article is dedicated to the models for different types of systems creation problem. Identificat...
Multivariable and closed-loop identification of large scale industrial processes is studied. The pro...
We propose a new probabilistic framework for nonparametric identification and estimation of dynamic ...