Results 41 to 50 of about 2,503,125 (316)
ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020 In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural networks which are all trained jointly for the task of communicating correlated sources through a network of noisy point ...
Liu, Litian +3 more
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Modelling the permeability of polymers: a neural network approach [PDF]
, 1994 In this short communication, the prediction of the permeability of carbon dioxide through different polymers using a neural network is studied. A neural network is a numeric-mathematical construction that can model complex non-linear relationships.
Bos, A. +6 more
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Prediction of subsidence due to underground mining by artificial neural networks [PDF]
, 2003 Alternatively to empirical prediction methods, methods based on influential functions and on mechanical model, artificial neural networks (ANNs) can be used for the surface subsidence prediction.
Ambrožič, Tomaž, Turk, Goran
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Neural Networks Architecture Evaluation in a Quantum Computer
, 2017 In this work, we propose a quantum algorithm to evaluate neural networks architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The proposed algorithm is based on a quantum associative memory and the learning algorithm for artificial
da Silva, Adenilton José +1 more
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Journal of Computer and System Sciences, 2001 28 pages, 11 figures, To appear in Journal of Computer and System ...
Sanjay Gupta, R. K. P. Zia
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Neural networks and contagion [PDF]
Revue d'économie industrielle, 2006 We analyze local as well as global interaction and contagion in population games, using the formalism of neural networks. In contrast to much of the literature, a state encodes not only the frequency of play, but also the spatial pattern of play. Stochastic best response dynamics with logistic noise gives rise to a log-linear or logit response model ...
Berninghaus, S. K. +2 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Spinal Cord Injury in Myelomeningocele: Prospects for Therapy
Frontiers in Cellular Neuroscience, 2020 Myelomeningocele (MMC) is the most common congenital defect of the central nervous system and results in devastating and lifelong disability. In MMC, the initial failure of neural tube closure early in gestation is followed by a progressive prenatal ...
Karolina Janik +3 more
doaj +1 more source
The neural network art which uses the Hamming distance to measure an image similarity score [PDF]
, 2019 This study reports a new discrete neural network of Adaptive Resonance Theory (ART-1H) in which the Hamming distance is used for the first time to estimate the measure of binary images (vectors) proximity.
Dmitrienko, V. D. +2 more
core
, 2018 We demonstrate the capability of a convolutional deep neural network in predicting the nearest-neighbor energy of the 4x4 Ising model. Using its success at this task, we motivate the study of the larger 8x8 Ising model, showing that the deep neural ...
Mills, Kyle, Tamblyn, Isaac
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