in recent years, researches on reinforcement learning (rl) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. neural network reinforcement learning (nnrl) is among the most popular algorithms in the rl framework. the advantage of using neural networks enables the rl to search for optimal policies more efficiently in several real-life applicat...

Merging the adaptive networks with the free space optical (FSO) communication technology is a very interesting field of research because by adding the benefits of this technology, the adaptive networks become more efficient, cheap and secure. This is due to the fact that FSO communication uses unregistered visible light bandwidth instead of the overused radio spectrum. However, in spite of all ...

this paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (mimo) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. the agents may have different dynamics and communicate together under a directed graph. a distributed adaptive method is designed for both cases. the structures of the contro...

The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...

In recent years, active filters have been considered and developed for elimation of harmonics in power networks. Comparing with passive, they are smaller and have better compensating characteristics and resistance to line distortions. In this paper, a novel idea based on adaptive filter theory in presented to develop an active filter to eliminate the distortions of an arbitrary signal. Using th...

In recent years, active filters have been considered and developed for elimation of harmonics in power networks. Comparing with passive, they are smaller and have better compensating characteristics and resistance to line distortions. In this paper, a novel idea based on adaptive filter theory in presented to develop an active filter to eliminate the distortions of an arbitrary signal. Using th...

the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...

in a detection network, the final decision is made by fusing the decisions from local detectors. the objective of that decision is to minimize the final error probability. to implement and optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. howev...

modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...