A study on neural network recognizer based on fuzzy rules and fuzzy inference fuzzy driven neural network recognizer in pattern recognition
Sang‐Hyeob Kim, Byoung‐Jun Park, Eun-Hye Jang, Myung‐Ae Chung · 2014
In this study, we introduce neural network recognizer based on fuzzy rules and fuzzy inference. The use of neural networks is proposed for efficient implementation of the fuzzy inference and the neural network is a trainable device consisting of some fuzzy rules and three processes, namely, premise, consequence and fuzzy inference processes. The premise process is driven by fuzzy c-means and the consequence processes deals with a polynomial function. A learning algorithm for the neural network recognizer is developed and its performance is compared with that of previous studies.