@inproceedings{14be815d45a346b985e0c38785e50b39,
title = "A recurrent interval type-2 fuzzy neural network with asymmetric membership functions for nonlinear system identification",
abstract = "This paper proposes a recurrent interval type-2 fuzzy neural network with asymmetric membership functions (RT2FNN-A). The RT2FNN-A uses the interval asymmetric type-2 fuzzy sets and it implements the FLS in a five layer neural network structure which contains four layer forward network and a feedback layer. Each asymmetric fuzzy member function (AFMF) is constructed by parts of four Gaussian functions. The corresponding learning algorithm is derived by gradient descent method. Finally, the RT2FNN-A is applied in identification of nonlinear dynamic system. Simulation results are shown to illustrate the effectiveness of the RT2FNN-A systems.",
author = "Lee, {Ching Hung} and Hu, {Tzu Wei} and Lee, {Chung Ta} and Lee, {Yu Chia}",
year = "2008",
doi = "10.1109/FUZZY.2008.4630570",
language = "English",
isbn = "9781424418190",
series = "IEEE International Conference on Fuzzy Systems",
pages = "1496--1502",
booktitle = "2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008",
note = "null ; Conference date: 01-06-2008 Through 06-06-2008",
}