Delayed Neural Networks
Delay-dependent passivity analysis of time-varying delayed neural networks with leakage and stochastic effects
... Moreover, neural networks with time delay in the leakage term also have great impact on the dynamics of stochastic neural networks because time delay in the stabilizing negative feedback term ...
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Adaptive almost surely asymptotically synchronization for stochastic delayed neural networks with Markovian switching
... stochastic delayed neural networks (SDNNs) with Markovian switch- ing have played an important role in the fields of science and engineering for their many practical applications, including image ...
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Stability Analysis for Uncertain Stochastic Delayed Neural Networks of Neutral-Type with Discrete and Distributed Delays
... for neural networks with time delays is of both practical and theoretical ...a neural network by creating oscillatory and instability ...for neural networks with time delays are ...
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Impulsive synchronization of drive response chaotic delayed neural networks
... The rest of this paper is organized as follows. In Section , we introduce the model and some preliminaries. In Section , we study the impulsive synchronization of drive- response chaotic delayed neural ...
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Robust exponential stability analysis for delayed neural networks with time varying delay
... In this paper, a global robust exponential stability of the delayed neural networks with time-varying delays is proposed. By constructing a suitable augmented Lyapunov func- tional, a delay-dependent ...
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Mixed \(H {\infty }/\)passive exponential function projective synchronization of delayed neural networks with hybrid coupling based on pinning sampled data control
... This paper presents the problem of mixed H ∞ /passive exponential function projective synchronization of delayed neural networks with constant discrete and distributed delay couplings under pinning ...
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Finite time anti synchronization of time varying delayed neural networks via feedback control with intermittent adjustment
... years, neural networks have become one of the most important nonlinear systems and have been intensively applied to solve various optimization problems ...as neural networks [– ...the ...
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Further analysis on stability of delayed neural networks via inequality technique
... of delayed neural networks is presented via the impulsive delay differential inequality, which was obtained by Li in recent ...delay neural networks are derived, and ...
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Projective synchronization of fractional order delayed neural networks based on the comparison principle
... memristor-based neural networks with time delays was discussed, but the theoretical synchronization results are poor and the sufficient conditions are ...fractional-order delayed neural ...
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Synchronization of a class of uncertain stochastic discrete time delayed neural networks
... type neural networks to guarantee the synchronization of drive system and response system in the models ...coupled networks has been analyzed in ...dynamical neural networks through ...
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Adaptive control of Mittag Leffler stabilization and synchronization for delayed fractional order BAM neural networks
... for neural networks, there are many parallel paths with different length and size of the nodes, because complex net- works have the features of time and space, single and coupled networks with time ...
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Deep Learning as a Frontier of Machine Learning: A Review
... artificial neural networks each has a specific property and can be applied in a different problem ...artificial neural networks have been used very popularly in many ...feedback neural ...
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Dynamic visual cryptography with Arnolds logarithm using ANN for medical data protection
... Artificial neural networks (ANNs) have been tested to solve many ...A Neural Network is a appliance that is perform to model the way in which the brain performs a work or function of ...propose ...
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Hopfield Neural Networks for Aircrafts’ Enroute Sectoring: KRISHAN-HOPES
... Conceptually Hopfield networks contain three important things or elements: basin of attraction, attractors, and trajectories. Furthermore Hopfield nets serve as content- addressable memory systems with binary ...
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Global Exponential Stability of Delayed Cohen Grossberg BAM Neural Networks with Impulses on Time Scales
... BAM neural networks with distributed delays and impulses on time ...BAM neural networks with distributed delays on time scales under the same ...
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Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network
... The accuracy of GRN reconstruction using synthetic gene expression data generated from the linear model are presented in Figs. 6, 7 and 8. These figures compare the Link F- score, Delay F-score and Effect F-score of the ...
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Data Mining using Neural Networks
... solving a problem through simulated annealing will prove incompatible with that of virtual machines or we can say that while working with virtualization of machines it will be quite incompatible with that of the features ...
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Recent trends in neuromorphic engineering
... on Neural Networks, the IEEE Transactions on Cybernetics, and is an Editor of the IETE Journal of ...and Neural Computing and Applications ...
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Recognizing Handwritten Alphabets using Neural Networks
... In the neural network, the error rate defines the deviation between the desired output and the actual output. Backpropagation algorithm tries to reduce the error rate. It works towards an optimal error rate at ...
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THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION
... J. Alamelu Mangai et al presented A Novel Feature Selection Framework for Automatic Web Page Classification [13]. Most of the classification algorithm’s performance depended on the elimination of the noisy and outlier ...
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