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

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 investi...

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Main Authors: 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
Format: Article
Language:English
Published: Springer International Publishing 2018
Subjects:
NA Architecture
T Technology (General)
Online Access:http://eprints.uthm.edu.my/5343/1/AJ%202018%20%28498%29.pdf
http://eprints.uthm.edu.my/5343/
http://dx.doi.org/10.1007/978-3-319-78437-3_2
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spelling my.uthm.eprints.53432022-01-09T04:06:06Z http://eprints.uthm.edu.my/5343/ From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications 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 NA Architecture T Technology (General) 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. This chapter describes a number of prominent applications built using the Kasabov’s NeuCube-based Spiking Neural Network (SNN) architecture for mapping, learning, visualization, classification/regression and better understanding and interpretation of SSTD. Springer International Publishing 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/5343/1/AJ%202018%20%28498%29.pdf Doborjeh, Maryam and Doborjeh, Zohreh and Gollahalli, Akshay Raj and Kumarasinghe, Kaushalya and Breen, Vivienne and Sengupta, Neelava and Ramos, Josafath Israel Espinosa and Hartono, Reggio and Capecci, Elisa and Kawano, Hideaki and Othman, Muhaini and Lei, Zhou and Jie, Yang and Bose, Pritam and Chenjie, Ge (2018) From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications. Practical Issues of Intelligent Innovations. pp. 17-36. ISSN 2198-4182 http://dx.doi.org/10.1007/978-3-319-78437-3_2
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic NA Architecture
T Technology (General)
spellingShingle NA Architecture
T Technology (General)
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
From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications
description 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. This chapter describes a number of prominent applications built using the Kasabov’s NeuCube-based Spiking Neural Network (SNN) architecture for mapping, learning, visualization, classification/regression and better understanding and interpretation of SSTD.
format Article
author 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
author_facet 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
author_sort Doborjeh, Maryam
title From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications
title_short From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications
title_full From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications
title_fullStr From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications
title_full_unstemmed From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications
title_sort from von neumann architecture and atanasoff’s abc to neuromorphic computation and kasabov’s neucube. part ii: applications
publisher Springer International Publishing
publishDate 2018
url http://eprints.uthm.edu.my/5343/1/AJ%202018%20%28498%29.pdf
http://eprints.uthm.edu.my/5343/
http://dx.doi.org/10.1007/978-3-319-78437-3_2
_version_ 1738581367471472640
score 13.211869

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