time-dependent neural networks
Robust stability of uncertain Markovian jump neural networks with mode dependent time varying delays and nonlinear perturbations
... jump neural networks with leakage delay, two additive time-varying delays, and nonlinear perturbations have been investi- ...between time-varying delays and their upper delay bounds is ...
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Parameter range dependent robust stability conditions for quaternion valued neural networks with time delays
... of neural networks with delays becomes more complicated and it may lead to volatility, in- stability and even ...quaternion-valued neural networks [14, ...
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Delay dependent stability criteria for neutral type neural networks with interval time varying delay signals under the effects of leakage delay
... In this paper, we investigated an improved stability criterion for neutral-type NNs with interval time-varying delay signal and leakage delay. For obtaining less conservative re- sults, some suitable LKFs under ...
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Passivity analysis of memristive neural networks with mixed time varying delays and different state dependent memductance functions
... Motivated by the works in [, , ] and the circuit design in [–], the main pur- pose of this paper is to establish the passivity criteria for the given memristive neural networks with mixed ...
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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 ...that time delays will affect stability of a neural network by creating oscillatory and instability ...for ...
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Delay-dependent passivity analysis of time-varying delayed neural networks with leakage and stochastic effects
... the time delay in the stabilizing negative feedback terms has a tendency to destabilize a system (This kind of delays is known as leakage delays or “forgetting” ...Moreover, neural networks with ...
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Quantum walk neural networks with feature dependent coins
... The choice of coin operators as well as the initial superposition of the walker control how this non-classical diffusion process evolves over the graph and therefore provides the deep learning technique additional ...
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Scaly Neural Networks for Speech Recognition Using DTW and Time Alignment Algorithms
... features. Neural Networks are, in essence, biologically inspired networks since they are based on the current understanding of the biological nervous ...of neural networks, and a basic ...
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New Results on Passivity Criteria for a Class of Neural Networks with Interval and Distributed Time-Varying Delays
... of neural networks with time-varying delay, see in [21], [24], ...of neural networks with discrete and distributed ...delay neural networks could be classified into two ...
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Delay probability distribution dependent stability criteria for discrete time stochastic neural networks with random delays
... the time delay is ...on time delays themselves, the variation interval and the distribution probability of the delay, that is, not only dependent on the time-delay interval, which ...
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Delay dependent optimal guaranteed cost control of stochastic neural networks with interval nondifferentiable time varying delays
... The outline of the paper is as follows. Section presents definitions and some well- known technical propositions, needed for the proof of the main result. LMI delay- dependent criteria for the guaranteed cost ...
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Evaluation of Mixed Deep Neural Networks for Reverberant Speech Enhancement
... recurrent neural networks, especially those with short and long term memory (LSTM), have presented surprising results in tasks related to time-dependent processing of signals, such as the ...
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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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Intrusion Detection System Using Hybrid Approach by MLP and K-Means Clustering
... introduce Neural Network Committee Machine (NNCM), it consist Input Reduction System which is based on Intrusion Detection System and Principal Component Analysis (PCA) and these are represented by three level ...
5
An Evolutionary Approach: Analysis of Artificial Neural Networks
... Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or ...
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Time-Dependent Influence Measurement in Citation Networks
... For systems which deal with measuring relations within social networks, especially these considering influence, obtaining ground-trust knowledge is a widely known problem. Indeed, influence is actually a ...
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Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE
... Deep Learning is a new domain of Machine learning research, with the objective of moving Machine Learning closer to human minds. In neural networks, there are two sets of neurons: ones that receive an input ...
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Data Mining on Romanian Stock Market Using Neural Networks for Price Prediction
... on neural networks and their financial application are published every ...the neural network development process. New models of Neural Networks are con- stantly presented but the most ...
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TIME SERIES FORECASTING USING NEURAL NETWORKS
... recurrent neural networks and training algorithms for predicting the exchange rate EUR/RON and ...of neural networks, a feed forward network and a recurrent network and compared their ...
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THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION
... multilayer neural network with GA for selecting IDF and ontology based features gave 93% of accuracy, high precision and recall and lowest RMSE when comparing to all other ...
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