Name
Title | ||
|---|---|---|
Estimating the characteristics of randomized dynamic data models (the Entropy-Robust Approach) |
Abstract | ||
|---|---|---|
We propose a new approach to finding dependencies between small volumes of input and output data based on randomized dynamic models and density estimation for the distributions of their parameters. Randomized dynamic models are defined by functional Volterra polynomials. To construct robust nonparametric estimation procedures, we develop an entropybased approach that employs functionals of generalized informational Boltzmann and Fermi entropies. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1134/S0005117914050063 | Automation and Remote Control |
Keywords | Field | DocType |
Entropy, Remote Control, Symbolic Computation, Distribution Density Function, Nonlinear Stochastic System | Density estimation,Mathematical optimization,Polynomial,Symbolic computation,Nonparametric statistics,Input/output,Dynamic data,Dynamic models,Boltzmann constant,Mathematics | Journal |
Volume | Issue | ISSN |
75 | 5 | 1608-3032 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu. S. Popkov | 1 | 2 | 2.46 |
| A. Yu. Popkov | 2 | 2 | 2.46 |
| Yu. N. Lysak | 3 | 1 | 0.96 |