Results 71 to 80 of about 142 (100)

An Online Intrusion Detection System to Cloud Computing Based on Neucube Algorithms

International Journal of Cloud Applications and Computing, 2018
This article describes how as network traffic grows, attacks on traffic become more complicated and harder to detect. Recently, researchers have begun to explore machine learning techniques with cloud computing technologies to classify network threats. So, new and creative ways are needed to enhance intrusion detection system.
Ammar Almomani, Mohammad Alauthman, Firas AlBalas, Osama M. Dorgham, Atef A. Obeidat   +4 more
openaire   +1 more source

Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model [PDF]

2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS), 2014
The proposed feasibility analysis introduces a new methodology for modelling and understanding functional Magnetic Resonance Image (fMRI) data recorded during human cognitive activity. This constitutes a type of Spatio-Temporal Brain Data (STBD) measured according to neurons spatial location inside the brain and their signals oscillating over the ...
Elisa Capecci, Nikola Kasabov, Maryam Doborjeh   +2 more
exaly   +2 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   +2 more sources

Classification of fMRI Data in the NeuCube Evolving Spiking Neural Network Architecture

2014
This paper presents a new method and a case study on fMRI spatio- and spectro-temporal data (SSTD) classification with the use of the recently proposed NeuCube architecture [1]. NeuCube is a three dimensional brain-like model of evolving spiking neurons that can be trained with SSTD such as fMRI, EEG and other brain data. This SSTD is mapped, analyzed,
Norhanifah Murli, Nikola K. Kasabov, Bana Handaga   +2 more
openaire   +1 more source

Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture

2015 International Joint Conference on Neural Networks (IJCNN), 2015
Epilepsy is the most diffuse brain disorder that can affect people's lives even on its early stage. In this paper, we used for the first time the spiking neural networks (SNN) framework called NeuCube for the analysis of electroencephalography (EEG) data recorded from a person affected by Absence Epileptic (AE), using permutation entropy (PE) features.
Elisa Capecci, Francesco Carlo Morabito, Jonas Duun-Henriksen   +2 more
exaly   +2 more sources

Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications

2014 International Joint Conference on Neural Networks (IJCNN), 2014
The paper is a feasibility analysis of using the recently introduced by one of the authors spiking neural networks architecture NeuCube for modelling and recognition of complex EEG spatio-temporal data related to both physical and intentional (imagined) movements.
Elisa Capecci, Denise Taylor, Zeng-Guang Hou   +2 more
exaly   +2 more sources

From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine

2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016
During the 1940s John Atanasoff with the help of one of his students Clifford E. Berry, in Iowa State College, created the ABC (Atanasoff-Berry Computer) that was the first electronic digital computer. The ABC computer was not a general-purpose one, but still, it was the first to implement three of the most important ideas used in computers nowadays ...
Nikola K. Kasabov, Neelava Sengupta, Nathan Matthew Scott   +2 more
openaire   +1 more source

NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation

2013
Classification and knowledge extraction from complex spatio-temporal brain data such as EEG or fMRI is a complex challenge. A novel architecture named the NeuCube has been established in prior literature to address this. A number of key points in the implementation of this framework, including modular design, extensibility, scalability, the source of ...
Nathan Matthew Scott, Nikola K. Kasabov, Giacomo Indiveri   +2 more
openaire   +2 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, Grace Y Wang, Nikola Kasabov   +2 more
exaly   +4 more sources

Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system [PDF]

2016 International Joint Conference on Neural Networks (IJCNN), 2016
This paper introduces a novel personalised modelling framework and system for analysing Spatio-Temporal Brain Data (STBD) along with person clinical static data. For every individual, based on selected subset of similar to this individual clinical data, a subset of STBD is used for training a personalised Spiking Neural Network (PSNN) model using the ...
Nikola Kasabov, Maryam Doborjeh
exaly   +2 more sources