Behavioral models of nonlinear filters based on discrete time cellular neural networks

Elena Solovyeva
2017 Vibroengineering PROCEDIA  
The nonlinear dynamic system modeling based on the input/output relationship results from solving the approximation problem. One can distinguish two large classes: polynomials and neural networks. The different types of neural networks draw attention. The discrete time feedforward cellular neural network is suggested for filtering non-Gaussian noise, as well as the example of nonlinear filters modeling to cancel the impulse noise is represented.
doi:10.21595/vp.2017.18660 fatcat:yiaobnqrdrbjza3imsjas6dm3q