Classification and regression of spatio-temporal signals using NeuCube and its realization on SpiNNaker neuromorphic hardware [PDF]
Journal of Neural Engineering, 2019 The objective of this work is to use the capability of spiking neural networks to capture the spatio-temporal information encoded in time-series signals and decode them without the use of hand-crafted features and vector-based learning and the realization of the spiking model on low-power neuromorphic hardware.The NeuCube spiking model was used to ...
Jan Behrenbeck +9 more
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Spiking neural networks for predictive and explainable modelling of multimodal streaming data with a case study on financial time series and online news. [PDF]
Sci Rep, 2023 In a first study, this paper argues and demonstrates that spiking neural networks (SNN) can be successfully used for predictive and explainable modelling of multimodal streaming data.
AbouHassan I +3 more
europepmc +4 more sources
Design of MRI structured spiking neural networks and learning algorithms for personalized modelling, analysis, and prediction of EEG signals. [PDF]
Sci Rep, 2021 This paper proposes a novel method and algorithms for the design of MRI structured personalized 3D spiking neural network models (MRI-SNN) for a better analysis, modeling, and prediction of EEG signals.
Saeedinia SA +3 more
europepmc +3 more sources
Case Study-Spiking Neural Network Hardware System for Structural Health Monitoring. [PDF]
Sensors (Basel), 2020 This case study provides feasibility analysis of adapting Spiking Neural Networks (SNN) based Structural Health Monitoring (SHM) system to explore low-cost solution for inspection of structural health of damaged buildings which survived after natural ...
Pang L +6 more
europepmc +4 more sources
NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals [PDF]
IAPR International Workshop on Artificial Neural Networks in Pattern Recognition, 2012 The brain functions as a spatio-temporal information processing machine and deals extremely well with spatio-temporal data. Spatio- and spectro-temporal data (SSTD) are the most common data collected to measure brain signals and brain activities, along with the recently obtained gene and protein data. Yet, there are no computational models to integrate
N. Kasabov
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Modelling Peri-Perceptual Brain Processes in a Deep Learning Spiking Neural Network Architecture. [PDF]
Sci Rep, 2018 Familiarity of marketing stimuli may affect consumer behaviour at a peri-perceptual processing level. The current study introduces a method for deep learning of electroencephalogram (EEG) data using a spiking neural network (SNN) approach that reveals ...
Gholami Doborjeh Z +3 more
europepmc +3 more sources
Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data [PDF]
International Conference on Neural Information Processing, 2015 The paper presents a novel clustering method for dynamic Spatio-Temporal Brain Data (STBD) on the case study of functional Magnetic Resonance Image (fMRI). The method is based on NeuCube spiking neural network (SNN) architecture, where the spatio-temporal relationships between STBD streams are learned and simultaneously the clusters are created.
Maryam Gholami Doborjeh, Nikola Kasabov
openaire +2 more sources
A spiking neural network model for obstacle avoidance in simulated prosthetic vision [PDF]
2014 International Joint Conference on Neural Networks (IJCNN), 2017 Limited by visual percepts elicited by existing visual prosthesis, it’s necessary to enhance its functionality to fulfill some challenging tasks for the blind such as obstacle avoidance.
Ge, Chenjie +3 more
core +3 more sources
Security and Communication Networks, Volume 2022, Issue 1, 2022., 2022 The virtually coupled train sets (VCTS) have been proposed to improve operational capability and passenger satisfaction and ensure punctuality, thus alleviating the rapidly worsening traffic pressure. Recently, due to the lack of reliable wireless communications and accurate perceptual information, VCTS based on industrial internet of things (IIoT) are
Shuomei Ma +4 more
wiley +1 more source
Journal of Advanced Transportation, Volume 2021, Issue 1, 2021., 2021 Traffic accident management as an approach to improve public security and reduce economic losses has received public attention for a long time, among which traffic accidents post‐impact prediction (TAPIP) is one of the most important procedures. However, existing systems and methodologies for TAPIP are insufficient for addressing the problem.
Duowei Li +3 more
wiley +1 more source