
In this paper, a method is presented for modelling a class of nonlinear systems which involves time-varying parameters. The system model proposed here is a type of nonlinear difference equation, where unknown parameters are assumed to be linearly involved in the system model. The principal line of attack is to assume that the nonlinear time varying function in the system can be expanded into the M known functions with unknown constant coefficients. First, the estimation process of unknown parameters is given by using the least squares method. Secondly, consistency properties and asymptotic normality conditions of the estimator are shown. Finally, two numerical examples are shown in order to demonstrate asymptotic properties of the estimator derived here.
| citations The total number of citations received by all articles of the researcher of interest. | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
