Name
Title | ||
|---|---|---|
Auxiliary Model-Based Forgetting Factor Stochastic Gradient Algorithm for Dual-Rate Nonlinear Systems and its Application to a Nonlinear Analog Circuit |
Abstract | ||
|---|---|---|
This paper studies the identification problem of dual-rate Hammerstein nonlinear systems. By means of the key-term separation principle, we develop a regression identification model with different input and output sampling rates. In order to promote the convergence rate of the stochastic gradient (SG) algorithm, an auxiliary model-based forgetting factor SG algorithm is derived. Finally, the proposed algorithm is applied to model a nonlinear analog circuit with dual-rate sampling and the simulation result shows the effectiveness of the algorithm. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s00034-013-9733-x | Circuits, Systems, and Signal Processing |
Keywords | Field | DocType |
Parameter estimation, Recursive identification, Hammerstein system, Dual-rate sampling, Gradient search, Key-term separation principle | Mathematical optimization,Nonlinear system,Regression,Separation principle,Control theory,Algorithm,Input/output,Sampling (statistics),Rate of convergence,Estimation theory,Parameter identification problem,Mathematics | Journal |
Volume | Issue | ISSN |
33 | 6 | 1531-5878 |
Citations | PageRank | References |
1 | 0.35 | 29 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangli Li | 1 | 25 | 2.22 |
| Lincheng Zhou | 2 | 27 | 3.92 |
| Ruifeng Ding | 3 | 261 | 11.82 |