Finding the capacity of Fuzzy Neural Networks (FNNs) via its equivalent fully connected neural networks (FFNNs)

The capacity of Fuzzy Neural Network (FNN) is explored in this paper. The FNN is first transformed into an equivalent fully connected three layer neural network, or FFNN, via a new approach proposed in this paper. Then the lower and upper bounds of FNN can be found. To check the validity of the theoretical bounds, an example is illustrated with the trainings to yield excellent capacity matching with the theoretical bounds. This new finding has its emerging values in all engineering applications using FNN, such as intelligent adaptive control, pattern recognition, and signal processing, ..., etc.