tthe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. this paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. as a novelty, the proposed controller employs a simple gaussian radial-basis-function network as an uncertainty estimator. the proposed netw...

background and aims: depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. so, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. use of this memory is latent in synthetic neuro-fuzzy algorithm. present article in...

Multiple radio access technologies (RATs) are available for the mobile users for the Internet connectivity. Traditional handover algorithms select the RAT based on the signal strength only. But quality of service (QoS) attributes are different for every application like VOIP requires lower network delay while video streaming application requires higher data rate. Therefore, these QoS parameters...

In recent years, there has been an expansive growth in the study and implementation of neural networks over a spectrum of research domains. Neural network based Predictive control is recognized as an efficient methodology to address difficult control problems. The NARMA model is an exact representation of the input-output behaviour of finite dimensional non-linear discrete time dynamical system...

in this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. utilizing the generalized characterization theorem. then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. here neural network is considered as a part of large eld called n...

In this paper, an automatic text–independent Arabic word speaker identification system is presented using Fuzzy Wavelet Neural Network terminology (FWNN). The approach is combining wavelet theory to fuzzy logic and neural network which lead to fabricate a Fuzzy Wavenet . Position and dilation of the fuzzy wavenets are fixed and the weights are optimized according to learning algorithm in the ne...

There exist problems in fuzzy finite element methods because technique of solving fuzzy equations is not perfect. For example, computation amount is too big and both sides of the equality are not exactly equal when solutions are substituted into the original equation. The concept of monosource fuzzy number is developed to simplify the calculation process of fuzzy equations. However the source o...

This paper deals with the design of a model reference direct inverse control that is applied to the liquid level process of a conical tank. We approximate the process by linear local models based on Takagi-Sugeno fuzzy modeling. Therefore, a fuzzy identification is performed by means of a fuzzy clustering algorithm. From the obtained fuzzy model and the specifications of the reference model, we...

By combining the fuzzy theory and neural network technology, a fuzzy neural network (FNN) is proposed in this paper, whose learning algorithms are developed by steep algorithm. The excitation system model based on FNN is also derived in this paper, which can be used for on-line and off-line analysis and control respectively. The simulation results demonstrate that the FNN models can give precis...