Results 31 to 40 of about 2,150,519 (283)
Scientific Reports, 2022 Working memory (WM) is a complex cognitive function involved in the temporary storage and manipulation of information, which has been one of the target cognitive functions to be restored in neurorehabilitation.
Jimin Park +3 more
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Recurrent neural network optimization for wind turbine condition prognosis
Diagnostyka, 2022 This research focuses on employing Recurrent Neural Networks (RNN) to prognosis a wind turbine operation’s health from collected vibration time series data, by using several memory cell variations, including Long Short Time Memory (LSTM), Bilateral LSTM (
Kerboua Adlen, Kelaiaia Ridha
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Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling [PDF]
, 2000 Copyright @ 2000 IEEEThis paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems.
Wang, D, Yang, S
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Neural network approximation [PDF]
Acta Numerica, 2021 Neural networks (NNs) are the method of choice for building learning algorithms. They are now being investigated for other numerical tasks such as solving high-dimensional partial differential equations. Their popularity stems from their empirical success on several challenging learning problems (computer chess/Go, autonomous navigation, face ...
DeVore, Ronald +2 more
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Static internal representation of dynamic situations reveals time compaction in human cognition
Journal of Advanced Research, 2021 Introduction: The human brain has evolved under the constraint of survival in complex dynamic situations. It makes fast and reliable decisions based on internal representations of the environment.
José Antonio Villacorta-Atienza +9 more
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Cephalopod Neural Networks [PDF]
Neurosignals, 2004 Cephalopods have arguably the largest and most complex nervous systems amongst the invertebrates; but despite the squid giant axon being one of the best studied nerve cells in neuroscience, and the availability of superb information on the morphology of some cephalopod brains, there is surprisingly little known about the operation of the neural ...
Roddy, Williamson, Abdesslam, Chrachri
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Frontiers in Systems Neuroscience, 2021 The hippocampus is crucial for forming associations between environmental stimuli. However, it is unclear how neural activities of hippocampal neurons dynamically change during the learning process.
Shogo Takamiya +12 more
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Journal of Computer and System Sciences, 2001 28 pages, 11 figures, To appear in Journal of Computer and System ...
Gupta, Sanjay, Zia, R.K.P.
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Neural Networks, 2019 It has been known for discrete-time recurrent neural networks (NNs) that binary-state models using the Heaviside activation function (with Boolean outputs 0 or 1) are equivalent to finite automata (level 3 in the Chomsky hierarchy), while analog-state NNs with rational weights, employing the saturated-linear function (with real-number outputs in the ...
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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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