Improved HTM Spatial Pooler with Homeostatic Plasticity Control
dc.contributor.author | Dobric, D | |
dc.contributor.author | Pech, A | |
dc.contributor.author | Ghita, B | |
dc.contributor.author | Wennekers, Thomas | |
dc.contributor.editor | Marsico MD | |
dc.contributor.editor | Baja GSD | |
dc.contributor.editor | Fred ALN | |
dc.date.accessioned | 2021-05-18T10:55:18Z | |
dc.date.available | 2021-05-18T10:55:18Z | |
dc.date.issued | 2021 | |
dc.identifier.isbn | 9789897584862 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/17130 | |
dc.description.abstract |
Hierarchical Temporal Memory (HTM) - Spatial Pooler (SP) is a Learning Algorithm for learning of spatial patterns inspired by the neo-cortex. It is designed to learn the pattern in a few iteration steps and to generate the Sparse Distributed Representation (SDR) of the input. It encodes spatially similar inputs into the same or similar SDRs memorized as a population of active neurons organized in groups called micro-columns. Findings in this research show that produced SDRs can be forgotten during the training progress, which causes the SP to learn the same pattern again and converts into the new SDR. This work shows that instable learning behaviour of the SP is caused by the internal boosting algorithm inspired by the homeostatic plasticity mechanism. Previous findings in neurosciences show that this mechanism is only active during the development of new-born mammals and later deactivated or shifted from cortical layer L4, where the SP is supposed to be active. The same mechanism was used in this work. The SP algorithm was extended with the new homeostatic plasticity component that controls the boosting and deactivates it after entering the stable state. Results show that learned SDRs remain stable during the lifetime of the Spatial Pooler. | |
dc.format.extent | 98-106 | |
dc.language.iso | en | |
dc.publisher | SCITEPRESS - Science and Technology Publications | |
dc.subject | Hierarchical Temporal Memory | |
dc.subject | Corticallearning Algorithm | |
dc.subject | Spatial Pooler | |
dc.subject | Homeostatic Plasticity | |
dc.title | Improved HTM Spatial Pooler with Homeostatic Plasticity Control | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000662835900010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.date-start | 2021-02-04 | |
plymouth.date-finish | 2021-02-06 | |
plymouth.publisher-url | http://www.informatik.uni-trier.de/~ley/db/conf/icpram/icpram2021.html | |
plymouth.conference-name | 10th International Conference on Pattern Recognition Applications and Methods | |
plymouth.publication-status | Published | |
plymouth.journal | Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods | |
dc.identifier.doi | 10.5220/0010314200980106 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Admin Group - REF | |
plymouth.organisational-group | /Plymouth/Admin Group - REF/REF Admin Group - FoSE | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.5220/0010314200980106 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |