Results 91 to 100 of about 142 (100)

From von Neumann Architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications

2018
Spatio/Spector-Temporal Data (SSTD) analyzing is a challenging task, as temporal features may manifest complex interactions that may also change over time. Making use of suitable models that can capture the “hidden” interactions and interrelationship among multivariate data, is vital in SSTD investigation.
Doborjeh, Maryam, Doborjeh, Zohreh, Gollahalli, Akshay Raj, Kumarasinghe, Kaushalya, Breen, Vivienne, Sengupta, Neelava, Ramos, Josafath Israel Espinosa, Hartono, Reggio, Capecci, Elisa, Kawano, Hideaki, Othman, Muhaini, Lei, Zhou, Jie, Yang, Bose, Pritam, Chenjie, Ge   +14 more
openaire   +2 more sources

NeuCube^(ST) for spatio-temporal data predictive modelling with a case study on ecological data

2014 International Joint Conference on Neural Networks (IJCNN), 2014
Zhenhong Jia, Muhaini Othman, Yuxiao Li   +2 more
exaly   +2 more sources

Brain-Inspired SNN for Deep Learning in Time-Space and Deep Knowledge Representation. NeuCube

2018
This chapter introduces brain-inspired evolving SNN (BI-SNN) in which both the SNN architecture and learning are inspired by the structure, organisation and learning in the human brain. BI-SNN manifest deep learning from data and deep knowledge representation inspired by human brain as discussed in Chap. 3 of the book.
openaire   +1 more source

A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer’s Disease EEG Data

2015
The paper presents a feasibility analysis of a novel Spiking Neural Network (SNN) architecture called NeuCube [10] for classification and analysis of functional changes in brain activity of Electroencephalography (EEG) data collected amongst two groups: control and Alzheimer’s Disease (AD).
Elisa Capecci, Francesco Carlo Morabito, Maurizio Campolo, Nadia Mammone, Domenico Labate, Nikola Kasabov   +5 more
openaire   +1 more source

Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture

2016
This paper is a feasibility study of using the NeuCube spiking neural network (SNN) architecture for modeling EEG brain data related to perceiving versus mimicking facial expressions. It is demonstrated that the proposed model can be used to study the similarity and differences between corresponding brain activities as complex spatio-temporal patterns.
Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola K. Kasabov, Maryam Gholami Doborjeh   +4 more
openaire   +1 more source

Izhikevich Neurons in NeuCube for Longitudinal Data Classification

Balkaran Singh, Sugam Budhraja, Maryam Doborjeh, Zohreh Doborjeh, Edmund M.-K. Lai, Nikola K. Kasabov   +5 more
openaire   +1 more source

From von Neumann Architecture and Atanasoffs ABC to Neuro-Morphic Computation and Kasabov’s NeuCube: Principles and Implementations

Studies in Computational Intelligence, 2018
Josafath Israel Espinosa Ramos, Stefan Marks, Neelava Sengupta   +2 more
exaly  

Integrating Local STDP and Global Backpropagation Learning Using Spike-Time and Spike-Rate Representations for Improved Classification of Spatiotemporal Data in the Neucube Brain Inspired Evolving Spiking Neural Network Architecture: A Case Study on EEG Brain Data

2023
Xuanle Zhou, Maryam Doborjeh, Nikola Kasabov, Zohreh Doborjeh   +3 more
openaire   +1 more source

Brain-Inspired SNN for Deep Learning in Time-Space and Deep Knowledge Representation. NeuCube

Springer Series on Bio- and Neurosystems, 2019
Nikola Kasabov, Kasabov Nikola K
exaly  

NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data.

Enmei Tu, Nikola K. Kasabov, Muhaini Othman, Yuxiao Li, Susan P. Worner, Jie Yang 0002, Zhenghong Jia   +6 more
openaire   +1 more source