Results 81 to 90 of about 751,622 (266)
Evolving Spiking Neural Networks for online learning over drifting data streams [PDF]
, 2018 Publisher Copyright: © 2018 Elsevier LtdNowadays huge volumes of data are produced in the form of fast streams, which are further affected by non-stationary phenomena.
Laña, Ibai +4 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
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 ...
openaire +3 more sources
Unsupervised Learning of Neural Networks to Explain Neural Networks
CoRR, 2018 This paper presents an unsupervised method to learn a neural network, namely an explainer, to interpret a pre-trained convolutional neural network (CNN), i.e., explaining knowledge representations hidden in middle conv-layers of the CNN. Given feature maps of a certain conv-layer of the CNN, the explainer performs like an auto-encoder, which first ...
Quanshi Zhang +4 more
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A broad class of discrete-time hypercomplex-valued hopfield neural networks
, 2020 In this paper, we address the stability of a broad class of discrete-time hypercomplex-valued Hopfield-type neural networks. To ensure the neural networks belonging to this class always settle down at a stationary state, we introduce novel hypercomplex ...
Valle, Marcos Eduardo +1 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang +10 more
wiley +1 more source
ARTIFICIAL NEURAL NETWORKS AND THEIR APPLICATIONS IN BUSINESS [PDF]
In modern software implementations of artificial neural networks the approach inspired by biology has more or less been abandoned for a more practical approach based on statistics and signal processing. In some of these systems, neural networks, or parts
Iordache Ana Maria Mihaela
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New necessary and sufficient conditions for absolute stability of neural networks
, 2007 This paper presents new necessary and sufficient conditions for absolute stability of asymmetric neural networks. The main result is based on a solvable Lie algebra condition, which generalizes existing results for symmetric and normal neural networks ...
Chu, Tianguang, Zhang, Cishen
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Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
APPLICATION OF NEURAL NETWORKS IN PREDICTIVE DATA MINING [PDF]
Neural Networks represent a meaningfully different approach to using computers in the workplace. A neural network is used to learn patterns and relationships in data. The data may be the results of a market research effort, or the results of a production
Saratha Sathasivam
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