Name
Title | ||
|---|---|---|
Blind nonlinear system identification based on a constrained hybrid genetic algorithm |
Abstract | ||
|---|---|---|
System identification is an important issue in communication, instrumentation, and control systems. In this paper, we proposed a method with higher-order cumulant fitting for nonlinear system identification. Compared with the conventional method, which uses second-order cumulant as a constraint, the proposed method uses fourth-order cumulant in order to smooth out the additive Gaussian noise. Since the cost function with higher-order statistics has local minima, we also propose to use a hybrid method of simplex and genetic algorithms to minimize the cost function. The applicability of the proposed method is demonstrated by the computer simulations. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/TIM.2003.814354 | IEEE T. Instrumentation and Measurement |
Keywords | Field | DocType |
blind nonlinear system identification,additive gaussian noise,identification,higher-order statistics,higher-order cumulant,hybrid genetic algorithm (ga),higher order cumulants (hocs),nonlinear systems,simplex algorithm,higher order statistics,nonlinear system,genetic algorithms,constraint,gaussian noise,blind system identification,computer simulation,constrained hybrid genetic algorithm,cost function,system identification,nonlinear system identification,control systems,indexing terms,cumulant,genetic algorithm,control system,local minima,higher order,second order | Mathematical optimization,Nonlinear system,Higher-order statistics,Nonlinear system identification,Maxima and minima,Control system,System identification,Gaussian noise,Genetic algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
52 | 3 | 0018-9456 |
Citations | PageRank | References |
5 | 0.97 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yen-Wei Chen | 1 | 720 | 155.73 |
| Shusuke Narieda | 2 | 19 | 9.15 |
| K. Yamashita | 3 | 5 | 0.97 |