Time delayed neural network
Symmetry discrete time delayed neural network
... In this paper, we consider a three-dimensional discrete neural network model with delay. The characteristic equation of the linearized system at the zero solution is a polynomial equation involving very ...
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SynFace—Speech-Driven Facial Animation for Virtual Speech-Reading Support
... A time-delayed neural network was used to estimate the face parameter trajectories from spectral features of speech, whereas an HMM phoneme recogniser was used to extract the phonetic ...
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Robust exponential stability analysis for delayed neural networks with time varying delay
... for neural networks with constant delays or time-varying delays were reported under some assumptions; for example, see [, , , , , , –] and references ...of delayed neural networks ...
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Hopf bifurcation analysis of a delayed five-neuron BAM neural network with two neurons in the X-layer
... artificial neural networks since Hopfield constructed a simplified neural network (NN) model ...As time delays always oc- cur in the signal transmission, Marcus and Westervelt proposed an NN ...
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Bifurcation and Chaos in Delayed Cellular Neural Network Model
... at time ( t − τ ) , τ is the signal transmission delay and c i (decay rate) is the rate with which the i th neuron will reset its potential to the resting state in isolation when disconnected from the ...
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Online Full Text
... discrete neural network with one neuron and a time de- lay is investigated in Section ...a delayed discrete neural network with two ...
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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 neural ...
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A generalized procedure in designing recurrent neural network identification and control of time varying delayed nonlinear dynamic systems
... of neural network as a reference mode to relive the complexity in nonlinear control system ...using neural network to approximate nonlinear systems and then using the reference plus linear ...
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Modeling multiple time units delayed gene regulatory network using dynamic Bayesian network.
... regulatory network from gene expression ...Boolean network was first applied to model gene regulatory network by Liang et ...boolean network model, all factors in a genetic regulatory ...
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Computational Intelligence based Data Driven Modeling: A case Study in Hydrology
... systems. Neural computing is one the important tools for modeling the nonlinear structures and efficiently applying in the measurement of inexplicit ...Dynamic Neural Network (DNN) models, based on ...
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Synchronization of a class of uncertain stochastic discrete time delayed neural networks
... same time, most of the papers mentioned above are concerned with continuous- time neural ...discrete-time neural networks have been investigated; see ...discrete-time ...
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Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network
... Diverse methods with different levels of complexity have been used to model, analyze and infer complex regulatory interactions [10–13]. Boolean networks are the simplest among them [14]. They are based only upon binary ...
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Robust Sliding Mode Control for Nonlinear Discrete Time Delayed Systems Based on Neural Network
... forward network such as multilayer perceptron (MLP), radial basis function (RBF) networks, Chebyshev neural network (CNN) ...MLP network has certain disadvantage that it requires a large ...
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Neural Network Based Time Delay Estimation
... constant time delay through the use of neural networks (NN) is ...a delayed, damped, and noisy replica of it are both filtered by a fourth-order digital infinite impulse response (IIR) ...estimated ...
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Research of adaptive control algorithm research based on rough set and implementation
... adaptive neural network algorithm has strong compatibility, some noise data, not including related function and reduce the input dimension, a fast learning process, uncertainty processing and force ...
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Journey time estimation using single inductive loop detectors on non signalised links
... The neural network models described here were built using NeuralWare’s ‘Predict’ software 17 which sits within Microsoft ...a neural network based on a set of data but manipulates, transforms ...
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Self organizing map and least square support vector machine method for river flow modelling
... flow time series data become increasingly popular (Kisi, 2008; 2009; Wang et ...flow time series data may lacking in an ability to provide physical interpretation and insight into catchment processes, they ...
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Research on Building Energy Consumption Prediction Method Based on LSTM Network
... LSTM neural network is better than that of traditional BP neural network through ...LSTM neural network with meteorological data can make the network dynamically adjusted, ...
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Short Term Load Forecasting With Feed Forward Neural Network Algorithm
... the network outputs with regard to the input-output patterns of the training ...the network after the ...A network is said to generalize well, when the output is correct (or close enough) for an ...
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Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia
... the time of input data (input) we have got, then it can be done to designing Artificial Neural Network modeling system which will be used to determine and recognize the pattern in predicting the ...
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