Results 21 to 30 of about 644,633 (264)
Design of a Configurable Spike-Encoding Circuit Based on Focal Plane Array
Applied Sciences, 2023 Spiking neural networks inspired by biological models are gaining popularity in artificial intelligence due to their ability to solve diverse problems while reducing energy consumption.
Di Lu +4 more
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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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Neural Plasticity, 2004 Functional and morphological studies in children affected by Attention Deficit Hyperactivity Disorder (ADHD) suggest a prefrontal cortex (PFc) dysfunction.
D. Viggiano +3 more
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Material Identification During Turning by Neural Network
Journal of Machine Engineering, 2020 A design concept for high-performance components involves the combination of different materials in hybrid workpieces. Different material properties and chemical compositions influence the machining quality of hybrid workpieces.
Berend DENKENA +3 more
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Tellus: Series A, Dynamic Meteorology and Oceanography, 2023 Many factors are affecting the downstream development of baroclinic waves, among which zonal shear flow is one of the factors that need to be considered.
Jian Song, Yu Ying Yang
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Boosting Neural Networks [PDF]
Neural Computation, 2000 Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, Ada Boost, has been applied with great success to several benchmark machine learning problems using mainly decision trees as base classifiers.
Holger Schwenk, Yoshua Bengio
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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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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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Neural network applications [PDF]
Proceedings Electronic Technology Directions to the Year 2000, 2002 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 character recognition and other engineering ...
Vonk, E., Jain, L.C., Veelenturf, L.P.J.
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