Results 81 to 90 of about 251 (118)

Exploring Types of Photonic Neural Networks for Imaging and Computing-A Review. [PDF]

Nanomaterials (Basel)
Khonina SN, Kazanskiy NL, Skidanov RV, Butt MA.   +3 more
europepmc   +1 more source

A 3D ray traced biological neural network learning model. [PDF]

Nat Commun
Yuen B, Dong X, Lu T.
europepmc   +1 more source

Artificial intelligence for brain disease diagnosis using electroencephalogram signals. [PDF]

J Zhejiang Univ Sci B
Shang S, Shi Y, Zhang Y, Liu M, Zhang H, Wang P, Zhuang L.   +6 more
europepmc   +1 more source

Nature-Inspired Intelligent Computing: A Comprehensive Survey. [PDF]

Research (Wash D C)
Jiao L, Zhao J, Wang C, Liu X, Liu F, Li L, Shang R, Li Y, Ma W, Yang S.   +9 more
europepmc   +1 more source

Improving NeuCube spiking neural network for EEG-based pattern recognition using transfer learning

Neurocomputing, 2023
Electroencephalogram (EEG) data are produced in quantity for measuring brain activity in response to external stimuli. With the rapid development of brain-inspired intelligence, spiking neural network (SNN) possesses the potential to handle EEG data by using spiking activity transmitted among spatially located synapses and neurons.
Yixiong Feng, Shanhe Lou, Bingtao Hu
exaly   +5 more sources

Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks

Studies in Computational Intelligence, 2018
This paper presents a new approach for spatio-temporal road traffic forecasting that relies on the adoption of the NeuCube architecture based on spiking neural networks. The NeuCube platform was originally conceived and designed to process electroencephalographic (EEG) signals considering their temporal component and their spatial source within the ...
Ibai Lana, Elisa Capecci, Javier Del Ser   +2 more
exaly   +3 more sources

Fault diagnosis for manipulators based on NeuCube

2015 11th International Conference on Natural Computation (ICNC), 2015
In this paper, a new fault diagnosis approach for manipulators based on spiking neural network is investigated. The newly proposed evolving spiking model is named NeuCube, it can be employed for classification, pattern recognition, and other kinds of problems.
Shiying Pan, Xiuqing Wang, Peng Zhang
exaly   +3 more sources

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment

Neural Networks, 2015
The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and more specifically on the analysis of the connectivity of a NeuCube model trained with ...
Elisa Capecci, Nikola Kasabov, Grace Y Wang   +2 more
exaly   +5 more sources