Article

GSTF Journal on Computing (JoC)

, 3:17

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Brief Study of Identification System Using Regression Neural Network Based on Delay Tap Structures

  • Alvin SahroniAffiliated withElectrical Engineering Department, UII Yogyakarta Email author 

Abstract

this investigation aims to provide an overview and investigations of non-linear identification system using neural network approach. Nowadays, a lot of neural network approach was done to provide a satisfying identification system. Backpropagation scheme as the mainstream approach for developing identification system has several limitations such as training data, computation time, architecture, optimization technique for weight value update, and many others. Regression Neural Network which is found by specht on 1990 contains more advantages compare with backpropagation scheme. With the improvement of computation time, architecture, and robustness of this model and provided 90% of effectiveness, promising a good prospective to develop non-linear identification system. For future works, it can be implemented in neural network predictive model control system and another control scheme based on identification system approach.

Keywords:

GRNN Identification System backpropagation predictive model