In this paper we present a fault detection strategy for wireless sensor networks. The strategy is based on modeling a sensor node by Takagi–Sugeno–Kang (TSK) fuzzy inference system (FIS), where a sensor measurement of a node is approximated by a function of the sensor measurements of the neighboring nodes. We also model a node by recurrent TSK-FIS (RFIS), where the sensor measurement of the nod...

A guidance law, based on supervisory recurrent fuzzy neural network control (SRFNNC), is proposed for the autonomous underwater vehicle (AUV) guidance systems. This SRFNNC system is comprised of a recurrent fuzzy neural network (RFNN) controller and a supervisory controller. The RFNN controller is used to mimic an ideal controller and the supervisory controller is designed to compensate for the...

A dynamic approach for modelling and simulation of motor unit discharge behaviour using recurrent fuzzy-techniques is presented. The model is able to generate a nominal force-time curve by means of the discharge behaviour of a single motor unit pool using the knowledge of various seemingly isolated findings that have been reported. In several simulations, it has been shown that recurrent fuzzy ...

Recurrent exponential fuzzy associative memories (RE-FAMs) are non-distributive memory models derived from the multivalued exponential recurrent associative memory (MERAM) of Chiueh and Tsai. A RE-FAM defines recursively a sequence of fuzzy sets obtained by a weighted average of the fundamental memories. In this paper, we show that the output of a single-step RE-FAM can be made as close as desi...

A improved parallel Recurrent Neural Network (RNN) model and an improved dynamic Backpropagation (BP) method of its learning, are proposed. The RNN model is given as a two layer Jordan canonical architecture for both continuous and discrete-time cases. The output layer is of Feedforward type. The hidden layer is a recurrent one with self-feedbacks and full forward connections with the inputs. A...

We often use recurrent fuzzy rule bases for describing of weak-formalized dynamic processes. There exist Mamdani and TakagiSugeno (TS) types that are distinguished with consequents organization. We consider in this paper 0 and 1 order TS models and Mamdani model in respect to investigation of chaotic behavior. It is well known that chaotic properties of dynamic system don’t allow to realize of ...

Nonlinear inter-symbol interference leads to significant error rate in nonlinear communication and digital storage channel. In this paper, therefore, a novel recurrent interval type-2 fuzzy neural network with asymmetric membership functions (RT2FNN-A) is proposed for nonlinear channel equalization. The RT2FNN-A uses the interval asymmetric type-2 fuzzy sets and it implements the fuzzy logic sy...

As a result from the demanding of process safety, reliability and environmental constraints, a called of fault detection and diagnosis system become more and more important. In this article some basic aspects of TSK (Takigi Sugeno Kang) neuro-fuzzy techniques for the prognosis and diagnosis of manufacturing systems are presented. In particular, a neuro-fuzzy model that can be used for the ident...