Name
Abstract | ||
|---|---|---|
A new method for identifying multiplicative parameters (i.e. the matrix-valued coefficients of the multiplicative state feedback) appearing in discrete-time bilinear models is proposed. The system is supposed to operate in a stochastic environment where the noisy output is the only sequence available for measurements. Ergodicity is not assumed, and the probability distributions involved may be arbitrary and unknown. A correlative identification technique is presented which uses stochastic approximation algorithms for estimating (with probability one) the unknown parameters. Simulated results are included. |
Year | DOI | Venue |
|---|---|---|
1984 | 10.1109/TSMC.1984.6313217 | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS |
Keywords | Field | DocType |
nonlinear systems,linear systems,parameter estimation | Mathematical optimization,Ergodicity,Multiplicative function,Control theory,Probability distribution,Estimation theory,System identification,Stochastic approximation,Mathematics,Discrete system,Bilinear interpolation | Journal |
Volume | Issue | ISSN |
14 | 2 | 0018-9472 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos S. Kubrusly | 1 | 14 | 4.30 |
| Carlos E. Pedreira | 2 | 60 | 6.51 |