Results 41 to 50 of about 9,085,112 (391)
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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Neural Network Acceptability Judgments [PDF]
Transactions of the Association for Computational Linguistics, 2018 This paper investigates the ability of artificial neural networks to judge the grammatical acceptability of a sentence, with the goal of testing their linguistic competence.
Alex Warstadt +2 more
semanticscholar +1 more source
Recognizing early MRI signs (or their absence) is crucial in diagnosing metachromatic leukodystrophy
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1999-2009, December 2022., 2022 Abstract Objectives Metachromatic leukodystrophy (MLD) has characteristic white matter (WM) changes on brain MRI, which often trigger biochemical and genetic confirmation of the diagnosis. In early or pre‐symptomatic disease stages, these typical MRI changes might be absent, hampering early diagnosis.
Daphne H. Schoenmakers +7 more
wiley +1 more source
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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Bootstrapping Neural Networks [PDF]
Neural Computation, 2000 Knowledge about the distribution of a statistical estimator is important for various purposes, such as the construction of confidence intervals for model parameters or the determination of critical values of tests. A widely used method to estimate this distribution is the so-called bootstrap, which is based on an imitation of the probabilistic ...
Franke, Jürgen, Neumann, Michael
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Neural Network Applications [PDF]
, 1995 Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in ...
Jain, L.C., Veelenturf, L.P.J., Vonk, E.
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The anterior nucleus of the thalamus plays a role in the epileptic network
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 2010-2024, December 2022., 2022 Abstract Objectives We investigated both the metabolic differences and interictal/ictal discharges of the anterior nucleus of the thalamus (ANT) in patients with epilepsy to clarify the relationship between the ANT and the epileptic network. Methods Nineteen patients with drug‐resistant epilepsy who underwent stereoelectroencephalography were studied ...
Hao Yan +9 more
wiley +1 more source
Correlational Neural Networks [PDF]
Neural Computation, 2016 Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)–based approaches and autoencoder (AE)–based approaches.
Sarath Chandar +3 more
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Variable neural networks for adaptive control of nonlinear systems [PDF]
, 1999 This paper is concerned with the adaptive control of continuous-time nonlinear dynamical systems using neural networks. A novel neural network architecture, referred to as a variable neural network, is proposed and shown to be useful in approximating the
Billings, S.A. +2 more
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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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