perceptron based neural networks
Gait Recognition Using Deep Learning
... Neural networks are predictive models loosely based on the action of biological ...name, neural networks are far from “thinking machines” or “artificial ...artifical neural ...
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Characterization of Lossy SIW Resonators Based on Multilayer Perceptron Neural Networks on Graphics Processing Unit
... Artificial Neural networks (ANNs) have been intensively employed to build smart model of microwave ...Multilayer Perceptron Neural Networks (MLPNNs) on Graphics Processing Unit (GPU), ...
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Algorithm and software based on MLPNN for estimating channel use in the spectral decision stage in cognitive radio networks
... 1958 based on the model of Mc-Culloch & Pitts and the error correction learning ...first Perceptron model was developed in a biological environment mimicking how the human eye works, hence its name ...
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A generalized ABFT technique using a fault tolerant neural network
... of neural networks is not suitably utilized by current common learning algorithms such as BP, in order to have or enhance fault tolerance in neural ...of neural network can be greatly improved ...
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A Comparative Study of Nonlinear Time Varying Process Modeling Techniques: Application to Chemical Reactor
... This paper proposes the design and a comparative study of two nonlinear systems modeling techniques. These two ap- proaches are developed to address a class of nonlinear systems with time-varying parameter. The first is ...
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Application of Artificial Neural Network and Adaptive Neural based Fuzzy Inference System Techniques in Estimating of Virtual Water
... Multilayer Perceptron (MLP), Radial Basis Functions (RBF), and Generalized Regression Neural Networks (GRNN) as well as ANFIS were examined in estimation of VW using measured data of the yield and ...
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APPLICATION OF MULTILAYER PERCEPTRON BASED ARTIFICIAL NEURAL NETWORK FOR MODELING OF RAINFALL RUNOFF IN A HIMALAYAN WATERSHED
... artificial neural network (ANN) models, multi layer feed-forward neural network using Levenberg–Marquardt learning algorithm (LMFF) and radial basis function (RBF) models for predicting daily watershed ...
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Short-term prediction of NO2 and NOx concentrations using multilayer perceptron neural network: a case study of Tabriz, Iran
... Artificial neural networks (ANNs) are able to approxi- mate accurately complicated nonlinear input–output re- lationships. Like their physics-based numerical model counterparts, ANNs require training ...
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Comparative Application of Radial Basis Function and Multilayer Perceptron Neural Networks to Predict Traffic Noise Pollution in Tehran Roads
... Network training and testing were performed using the same datasets applied to the MLP net- work. In order to increase the accuracy of RBF network, two parameters should be optimized: Spread and Maximum Number of Neurons ...
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Prediction of the pharmaceutical solubility in water and organic solvents via different soft computing models
... of neural networks: multilayer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM) based on the group contribution method (GC) and particle swarm optimization ...
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System identification of hammerstein model a quarter car passive suspension systems using Multilayer Perceptron Neural Networks (MPNN)
... In this paper, the error is assumed to have a Gaussian distribution. The cost function is minimized by applying the maximum likelihood parameter estimation technique [5-7]. The iterative weighted least squares algorithm ...
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Reducing Error Signal in Multilayer Perceptron Neural Networks using MLP for Label Ranking
... is based on fully connected feed-forward ...Several networks with one and two hidden layers, with different number of nodes in each hidden layer, have been ...multilayer perceptron with two hidden ...
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Estimation of soil parameters over bare agriculture areas from C band polarimetric SAR data using neural networks
... technique based on multi-layer perceptron (MLP) neural networks was ...The neural networks were trained and validated on a noisy simulated dataset generated from the Integral ...
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Identification and Prediction of Internet Traffic Using Artificial Neural Networks
... In this paper we present an artificial neural network (ANN) model based on the multi-layer perceptron (MLP) for analyzing internet traffic over IP networks. We used the input and output data ...
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Numerical Solution of Sixth Order Differential Equations Arising in Astrophysics by Neural Network
... Hopfield neural network ...forward neural network. Artificial neural networks based on Broyden-Fletcher-Goldfarb-Shanno (BF GS) optimization technique for solving ordinary and partial ...
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Efficiency of Multilayer Perceptron Neural Networks Powered by Multi Verse Optimizer
... BPA shows good performance when handling wide range of questions, but it suffers an important weakness. The algorithm is based on gradient descent concept. So, if the initial weights, or even any coming weights, ...
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Advanced approach to numerical forecasting using artificial neural networks
... is based on learning values from past periods and then approximating the future ...cial neural network, learning rule, types of activation function, number of inputs, length and also structure of input time ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks become ap- parent only for large-scale problems, which are computationally intensive and not feasible for hand ...MATLAB, neural network al- gorithms can be quickly implemented, ...
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Open Journal Systems
... models--Multilayer Perceptron (MLP), M5P and Linear Regression--were trained and tested in all possible combinations of targets and training periods from the weather data collected between the year 2002 and 2015 ...
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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 ...SVM based application VLSI ASIC, that contained an A/D converter using a bank of analog SVM ...and ...
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