Fuzzy continuous function and its properties
Fuzzy Sets and Systems
Can fuzzy neural nets approximate continuous fuzzy functions?
Fuzzy Sets and Systems
The fuzzy neural network approximation lemma
Fuzzy Sets and Systems
Computer Arithmetic in Theory and Practice
Computer Arithmetic in Theory and Practice
A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks
Information Sciences: an International Journal
Interval type-2 fuzzy logic and modular neural networks for face recognition applications
Applied Soft Computing
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Approximation of level continuous fuzzy-valued functions by multilayer regular fuzzy neural networks
Mathematical and Computer Modelling: An International Journal
IEEE Transactions on Neural Networks
Advances in Fuzzy Systems
| Hi-index | 0.01 |
The main purpose of this study is to state conditions that guarantee an interval type-2 triangular fuzzy (IT2TF) neural network can approximate continuous IT2TF functions. To make a more efficient calculation with IT2TF numbers, the sum and the product of two IT2TF numbers are constructed. These concepts are used in the definition of IT2TF polynomials. Moreover, the present study provides a mathematical framework to show that IT2TF polynomials are a compact Hausdroff space. Based on this concept we establish an interval type-2 fuzzy neural networks version of the Stone-Weierstrass theorem which enables approximation by a special class of IT2TF neural networks on the set of all monotonic and continuous IT2TF functions. Finally, a numerical example is given to illustrate the results.