Synchronization is very important for the efficient processing and transmission of information across the nervous system. Synchronization processes are ubiquitous in nature and play a very important role in many areas. As a special neural networks, fuzzy neural networks have an automatic adaption procedure and attract many attentions to their dynamical behaviors. In this paper, delayed fuzzy hi...

Fuzzy techniques have been originally designed to describe imprecise (“fuzzy”) expert knowledge. Somewhat surprisingly, fuzzy techniques have also been successfully used in situations without expert knowledge, when all we have is data. In this paper, we explain this surprising phenomenon by showing that the need for optimal processing of data (including crisp data) naturally leads to fuzzy and ...

Though traditional neural networks and fuzzy logic are powerful universal approximators, however without some refinements, they may not, in general, be good approximators for adaptive systems. By extending fuzzy sets to qualitative fuzzy sets, fuzzy logic may become universal approximators for adaptive systems. Similar considerations can be extended to neural networks.

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. The...

The goal of this work is to compare fuzzy, neural network and neuro-fuzzy approaches to the control of mobile robots. The rst part of this paper is devoted to the formal framework of fuzzy controllers. Results of an example of their use for a mobile robot are discussed. As an experimental platform, the Khepera mobile robot is used. The same example is studied using artiicial neural networks. Fo...

Fuzzy associative memories belong to the class of fuzzy neural networks that employ fuzzy operators such as fuzzy conjunctions, disjunctions, and implications in order to store associations of fuzzy patterns. Fuzzy associative memories are generally used to implement fuzzy rule-based systems. Applications of FAMs include backing up a truck and trailer, target tracking, human-machine interfaces,...

This paper gives a short introduction into Fuzzy Set Theory, presents an overview on fuzzy controllers, and discusses possible combinations between fuzzy controllers and neural networks. Fuzzy Sets suggested by L.A. Zadeh 32] ooer a possibility to formally describe linguistic expressions like tall, fast, medium, etc., and to operate on them. Fuzzy controllers use fuzzy sets to represent linguis...

to use soil hydrology processes (shp) models, which have increasingly extended during the last years, comprehensive knowledge about these models and their modeling approaches seems to be necessary. the modeling approaches can be categorized as either classical or non-classical. classical approaches mainly model the shp through solving the general unsaturated flow (richards) equation, numericall...

The paper presents a general framework of connectionistbased, intelligent decision support systems and its realisation with the use of fuzzy neural networks FuNNs and evolving fuzzy neural networks EFuNNs. FuNNs and EFuNNs facilitate learning from data, fuzzy rule insertion, rule extraction, and adaptation. Several applications of this framework on real problems are presented as case studies, t...

Although CO2 injection is one of the most common methods in enhanced oil recovery, it could alter fluid properties of oil and cause some problems such as asphaltene precipitation. The maximum amount of asphaltene precipitation occurs near the fluid pressure and concentration saturation. According to the description of asphaltene deposition onset, the bubble point pressure has a very special imp...