Working memory (WMCognitive workload (CWLClassification methodsMachine learningElectronic medical records (EMRPhysiciansThe objective of this research was to compare classification methods aimed at predicting w
This work examines the application of machine learning (ML) algorithms to evaluate dissolved gas analysis (DGA) data to quickly identify incipient faults in oil-immersed transformers (OITs). Transformers are pivotal equipment in the transmission and dist
P. An Electronic Synapse Device Based on Metal Oxide Resistive Switching Memory for Neuromorphic Computation. IEEE Trans. Elect. Dev. 58, 2729–2737 (2011). Article Google Scholar Ohno, T. et al. Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. Nat. ...
Electroencephalograph (EEG), the representation of the brain's electrical activity, is a widely used measure of brain activities such as working memory during cognitive tasks. Varying in complexity of cognitive tasks, mental load results in different EEG recordings. Classification of mental load is ...
Specifically for EEG classification for BCI, some approaches are based on deep learning. For example, Gao et al. constructed a convolutional neural network with long short-term memory (CNN-LSTM) framework, which allows extracting the spectral, spatial, and temporal features of EEG signals, to ach...
Therefore, data are accessed one time from the memory and then the rule is created depending on the evolution of the profile if the characteristics of the phishing e-mail have been changed. PECM is a clustering-based learning model that adaptive Evolving Clustering Method to distinguish between ...
Sandwith/cipó-cravo (ER2003) Improving memory and calming – Sap (water-soluble) – Burseraceae Protium amazonicum (Cuatrec.) Daly/breu-branco (JFLS413) Headache, stroke and disease of the air – Resin (fat-soluble) – triterpenes α-Amyrin, β-amyrina,b,d Protium aracouchini (Aubl....
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memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue ...
which become more notable for more complex networks with a large number of neuron layers. Furthermore, for digital implementation platforms, the raw input data usually need to be converted to the electrical domain, digitized and processed. Often, a large memory unit is required to store the data...