ABSTRACT
In this chapter, the authors discuss the structure of fuzzy neural networks and deal with general definitions of multifactorial functions. They show that a fuzzy neuron can be formulated by means of standard multifactorial function. The authors provide definitions of a fuzzy neural network based on fuzzy relationship and fuzzy neurons. They describe a learning algorithm for a fuzzy neural network based on ∨ and ∧ operations. Neural networks alone have demonstrated their ability to classify, recall, and associate information. There are several ways to classify fuzzy neural networks: a fuzzy neuron with crisp signals used to evaluate fuzzy weights, a fuzzy neuron with fuzzy signals which is combined with fuzzy weights, and a fuzzy neuron described by fuzzy logic equations.
