Publication: Synaptic interference channel
dc.contributor.coauthor | N/A | |
dc.contributor.department | Department of Electrical and Electronics Engineering | |
dc.contributor.department | Graduate School of Sciences and Engineering | |
dc.contributor.kuauthor | Akan, Özgür Barış | |
dc.contributor.kuauthor | Malak, Derya | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.schoolcollegeinstitute | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
dc.date.accessioned | 2024-11-09T23:49:15Z | |
dc.date.issued | 2013 | |
dc.description.abstract | Synaptic channels automatically adapt their weights to compensate for the variations resulted from the input and output characteristics, i.e., spike frequency, time correlation among inputs, time difference between presynaptic and postsynaptic action potentials. Modification of the synaptic conductances, i.e., channel weights, is the main mechanism that enables learning in neurons. In this paper, we approach this learning mechanism from a different perspective. First, we analyze the single-input single-output (SISO) and multi-input single-output (MISO) synaptic interference channels, and achievable communication rates. Furthermore, we provide the natural adaptive weight update algorithm for neurons based on experimental findings. Our results demonstrate that neurons are capable of mitigating the interference, and achieve rates close to the capacity. | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | N/A | |
dc.description.sponsorship | Turkish Scientific and Technical Research Council [109E257] | |
dc.description.sponsorship | Turkish National academy of Sciences Distinguished Young Scientist award Program (TUBa-GEBIP) | |
dc.description.sponsorship | IBM through IBM Faculty award This work was supported in part by the Turkish Scientific and Technical Research Council Career award under grant #109E257 and by the Turkish National academy of Sciences Distinguished Young Scientist award Program (TUBa-GEBIP) and by IBM through IBM Faculty award. | |
dc.identifier.doi | 10.1109/ICCW.2013.6649337 | |
dc.identifier.isbn | 9781-4673-5753-1 | |
dc.identifier.scopus | 2-s2.0-84890868435 | |
dc.identifier.uri | https://doi.org/10.1109/ICCW.2013.6649337 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/14343 | |
dc.identifier.wos | 572825900148 | |
dc.keywords | Action potentials | |
dc.keywords | Communication rate | |
dc.keywords | Input and output characteristics | |
dc.keywords | Interference channels | |
dc.keywords | Learning mechanism | |
dc.keywords | Single-input | |
dc.keywords | Single-output | |
dc.keywords | Synaptic conductance | |
dc.keywords | Time correlations | |
dc.keywords | Electrophysiology | |
dc.keywords | Neurons | |
dc.keywords | Signal interference | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.relation.ispartof | 2013 IEEE International Conference on Communications Workshops, ICC 2013 | |
dc.subject | Engineering | |
dc.subject | Electrical and electronic engineering | |
dc.subject | Telecommunications | |
dc.title | Synaptic interference channel | |
dc.type | Conference Proceeding | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Malak, Derya | |
local.contributor.kuauthor | Akan, Özgür Barış | |
local.publication.orgunit1 | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
local.publication.orgunit1 | College of Engineering | |
local.publication.orgunit2 | Department of Electrical and Electronics Engineering | |
local.publication.orgunit2 | Graduate School of Sciences and Engineering | |
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