Modified Stochastic Gradient Parameter Estimation Algorithms for a Nonlinear Two-variable Difference System
- Resource Type
- Article
- Authors
- Bin Jiang; Jing Chen
- Source
- (2022): 1493-1500.
- Subject
- Language
- Korean
- ISSN
- 15986446
This paper proposes a stochastic gradient algorithm and two modified stochastic gradient algorithms fora nonlinear two-variable difference system. The output and the input of a two-variable parameter system depend ontime and on spatial coordinates. A stochastic gradient algorithm is introduced to estimate the unknown parameters. In order to increase the convergence rate but not to increase the computational effort, two modified stochasticgradient algorithms are also proposed. The simulation results indicate that the proposed methods are effective.
This paper proposes a stochastic gradient algorithm and two modified stochastic gradient algorithms fora nonlinear two-variable difference system. The output and the input of a two-variable parameter system depend ontime and on spatial coordinates. A stochastic gradient algorithm is introduced to estimate the unknown parameters. In order to increase the convergence rate but not to increase the computational effort, two modified stochasticgradient algorithms are also proposed. The simulation results indicate that the proposed methods are effective.