Analysis of Type-2 Fuzzy Recurrent Wavelet Neural Network to Identify Non-linear dynamic System

This piece of work proposes a novel Type-2Fuzzy Recurrent Wavelet Neural Network (T2FWNN) to estimate the nonlinear systems. Such analysis facilitates to solve several realworld issues such as control and power system design and development, industrial sectors, broadband networks, etc. An extensive investigation of the nonlinear systems has been carried out to test the performance of the proposed T2FWNN model in estimating non-linear systems. The networks have been compared in terms of the error parameters, rate of convergence, and computational complexity. The novel structure has been shown to outperform other conventional techniques in modelling non-linear systems. It has witnessed a better convergence, low error, and faster response as revealed from our results.