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...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer International Publishing
2018
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| Online Access: | http://eprints.uthm.edu.my/5343/1/AJ%202018%20%28498%29.pdf |
| _version_ | 1825710007483629568 |
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| 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 |
| collection | UTHM |
| 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. |
| first_indexed | 2024-03-05T21:51:04Z |
| format | Article |
| id | uthm.eprints-5343 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:51:04Z |
| publishDate | 2018 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | 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 |
| 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 |
| title | 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_short | 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 |
| topic | NA Architecture T Technology (General) |
| url | http://eprints.uthm.edu.my/5343/1/AJ%202018%20%28498%29.pdf |
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