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time-delayed neural networks

Synchronization of a class of uncertain stochastic discrete time delayed neural networks

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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Delay-dependent passivity analysis of time-varying delayed neural networks with leakage and stochastic effects

Delay-dependent passivity analysis of time-varying delayed neural networks with leakage and stochastic effects

... for delayed stochastic neural networks can be classified into two categories: namely, delay-dependent and delay-independent ...the time delay is small, because of this physical reason much ...

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Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network

Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network

... a time-delayed GRN which takes into account the non-linearity of gene interaction and the noise of temporal ...Recurrent Neural Networks (RNNs) are computational tools inspired by the ...

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Global Exponential Stability of Delayed Cohen Grossberg BAM Neural Networks with Impulses on Time Scales

Global Exponential Stability of Delayed Cohen Grossberg BAM Neural Networks with Impulses on Time Scales

... on time scales, the homeomorphism theory, Lyapunov functional method, and some analysis techniques, sufficient conditions are obtained for the existence, uniqueness, and global exponential stability of the ...

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Impulsive synchronization of drive response chaotic delayed neural networks

Impulsive synchronization of drive response chaotic delayed neural networks

... drive-response neural networks with time-varying delays via impulsive ...different neural networks and relax the restrictions on the impulsive ...

11

Symmetry discrete time delayed neural network

Symmetry discrete time delayed neural network

... The presence of symmetries changes the nature and type of bifurcations that a dynam- ical system may undergo. There is a lot of research into equivariant bifurcations of ODEs. We refer the readers to Golubitsky []. But, ...

10

Further analysis on stability of delayed neural networks via inequality technique

Further analysis on stability of delayed neural networks via inequality technique

... 25. Li, X: Existence and global exponential stability of periodic solution for impulsive Cohen Grossberg-type BAM neural networks with continuously distributed delays. Appl Math Comput. 215, 292 – 307 ...

12

Projective synchronization of fractional order delayed neural networks based on the comparison principle

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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Global Mittag Leffler synchronization of delayed fractional order memristive neural networks

Global Mittag Leffler synchronization of delayed fractional order memristive neural networks

... This paper deals with the global Mittag-Leffler synchronization of fractional-order memristive neural networks (FMNNs) with time delay. Since the FMNNs are essentially a class of switched systems with ...

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NEW SUFFICIENT CRITERIA FOR GLOBAL ROBUST STABILITY OF NEURAL NETWORKS WITH MULTIPLE TIME DELAYS

NEW SUFFICIENT CRITERIA FOR GLOBAL ROBUST STABILITY OF NEURAL NETWORKS WITH MULTIPLE TIME DELAYS

... Abstract. In this paper, we study global robust asymptotic stability of the equilibrium point for neural networks with multiple time delays. By employing suitable Lyapunov functionals, we derive a ...

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Robust exponential stability analysis for delayed neural networks with time varying delay

Robust exponential stability analysis for delayed neural networks with time varying delay

... Remark  In this paper, we are mainly concerned with exponential stability. For this rea- son another practical background and other definitions have not been introduced. Among them, exponential stability provides a ...

16

Stability of delay neural networks with uncertainties via delayed intermittent control

Stability of delay neural networks with uncertainties via delayed intermittent control

... hybrid-coupled delayed dynamical ...mixed time varying ...in neural networks because of the external disturbances or the modeling inac- ...troducing time delays in control schemes can ...

19

Finite time anti synchronization of time varying delayed neural networks via feedback control with intermittent adjustment

Finite time anti synchronization of time varying delayed neural networks via feedback control with intermittent adjustment

... on neural networks and some relevant theoretical results have been established ...of neural networks have based themselves on the convergence time being large ...infinite time is ...

16

Finite time synchronization problems of delayed complex networks with stochastic perturbations

Finite time synchronization problems of delayed complex networks with stochastic perturbations

... a neural network sometimes has finite modes, so that switching from one to another at different times may occur [, ...complex networks can be regarded as a special class of stochastic network ...complex ...

13

Global Asymptotic Stability for a New Class of Neutral Neural Networks

Global Asymptotic Stability for a New Class of Neutral Neural Networks

... of neural cells, many dynamic neural networks are described by neutral functional differential equations including neutral delay differential ...These neural networks are called neutral ...

6

Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE

Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE

... as neural coding which attempts to define a relationship between various stimuli and associated neuronal responses in the ...deep neural networks, convolutional deep neural networks, ...

5

Intrusion Detection System Using Hybrid Approach by MLP and K-Means Clustering

Intrusion Detection System Using Hybrid Approach by MLP and K-Means Clustering

... A neural network is type of network as a set of distributed units following by a particular topology ...artificial neural network functions are used in different model proposed by different author [6, ...

5

Dynamic visual cryptography with Arnolds 
		logarithm using ANN for medical 
		data protection

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 ...

5

An Introduction to Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials

An Introduction to Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials

... The two-layer net that was partially hand crafted in Section 4.5.2 to solve the fourway classification problem can now be retrained in toto using backpropagation. Further, the same problem may be recast to demonstrate ...

317

Artificial Intelligence Applied to Project Success: A Literature Review

Artificial Intelligence Applied to Project Success: A Literature Review

... with neural networks in order to get a mapping between managerial elements of project management and project management ...between neural networks and regression analysis tools for identifying ...

6

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