FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3216108926> ?p ?o ?g. }

• W3216108926 endingPage "16" @default.
• W3216108926 startingPage "1" @default.
• W3216108926 abstract "As a new brain-inspired computational model of artificial neural networks, spiking neural networks transmit and process information via precisely timed spike trains. Constructing efficient learning methods is a significant research field in spiking neural networks. In this paper, we present a supervised learning algorithm for multilayer feedforward spiking neural networks; all neurons can fire multiple spikes in all layers. The feedforward network consists of spiking neurons governed by biologically plausible long-term memory spike response model, in which the effect of earlier spikes on the refractoriness is not neglected to incorporate adaptation effects. The gradient descent method is employed to derive synaptic weight updating rule for learning spike trains. The proposed algorithm is tested and verified on spatiotemporal pattern learning problems, including a set of spike train learning tasks and nonlinear pattern classification problems on four UCI datasets. Simulation results indicate that the proposed algorithm can improve learning accuracy in comparison with other supervised learning algorithms." @default.
• W3216108926 created "2021-12-06" @default.
• W3216108926 creator A5007976433 @default.
• W3216108926 creator A5068620302 @default.
• W3216108926 creator A5078704613 @default.
• W3216108926 date "2021-11-24" @default.
• W3216108926 modified "2023-10-18" @default.
• W3216108926 title "Supervised Learning Algorithm for Multilayer Spiking Neural Networks with Long-Term Memory Spike Response Model" @default.
• W3216108926 cites W101771737 @default.
• W3216108926 cites W1498436455 @default.
• W3216108926 cites W1516529420 @default.
• W3216108926 cites W1965678517 @default.
• W3216108926 cites W1970109917 @default.
• W3216108926 cites W1974983944 @default.
• W3216108926 cites W1976619609 @default.
• W3216108926 cites W2016639237 @default.
• W3216108926 cites W2017972389 @default.
• W3216108926 cites W2042013578 @default.
• W3216108926 cites W2054113233 @default.
• W3216108926 cites W2107433900 @default.
• W3216108926 cites W2114155871 @default.
• W3216108926 cites W2130459697 @default.
• W3216108926 cites W2130974072 @default.
• W3216108926 cites W2142770417 @default.
• W3216108926 cites W2152280100 @default.
• W3216108926 cites W2154616847 @default.
• W3216108926 cites W2155488283 @default.
• W3216108926 cites W2165639766 @default.
• W3216108926 cites W2170968634 @default.
• W3216108926 cites W2250145117 @default.
• W3216108926 cites W2512805308 @default.
• W3216108926 cites W2569813014 @default.
• W3216108926 cites W2611039260 @default.
• W3216108926 cites W2730906708 @default.
• W3216108926 cites W2892632544 @default.
• W3216108926 cites W2924112519 @default.
• W3216108926 cites W2929420007 @default.
• W3216108926 cites W2945308847 @default.
• W3216108926 cites W2963335874 @default.
• W3216108926 cites W2964035021 @default.
• W3216108926 cites W3006966652 @default.
• W3216108926 cites W3023328046 @default.
• W3216108926 cites W3035503061 @default.
• W3216108926 cites W3095297407 @default.
• W3216108926 cites W3102087395 @default.
• W3216108926 cites W3122696093 @default.
• W3216108926 cites W4213256231 @default.
• W3216108926 cites W4238614602 @default.
• W3216108926 doi "https://doi.org/10.1155/2021/8592824" @default.
• W3216108926 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34868299" @default.
• W3216108926 hasPublicationYear "2021" @default.
• W3216108926 type Work @default.
• W3216108926 sameAs 3216108926 @default.
• W3216108926 citedByCount "5" @default.
• W3216108926 countsByYear W32161089262022 @default.
• W3216108926 countsByYear W32161089262023 @default.
• W3216108926 crossrefType "journal-article" @default.
• W3216108926 hasAuthorship W3216108926A5007976433 @default.
• W3216108926 hasAuthorship W3216108926A5068620302 @default.
• W3216108926 hasAuthorship W3216108926A5078704613 @default.
• W3216108926 hasBestOaLocation W32161089261 @default.
• W3216108926 hasConcept C11413529 @default.
• W3216108926 hasConcept C115903868 @default.
• W3216108926 hasConcept C11731999 @default.
• W3216108926 hasConcept C119857082 @default.
• W3216108926 hasConcept C127413603 @default.
• W3216108926 hasConcept C133731056 @default.
• W3216108926 hasConcept C136389625 @default.
• W3216108926 hasConcept C153180895 @default.
• W3216108926 hasConcept C153258448 @default.
• W3216108926 hasConcept C154945302 @default.
• W3216108926 hasConcept C177264268 @default.
• W3216108926 hasConcept C199360897 @default.
• W3216108926 hasConcept C2779127903 @default.
• W3216108926 hasConcept C2781390188 @default.
• W3216108926 hasConcept C38858127 @default.
• W3216108926 hasConcept C41008148 @default.
• W3216108926 hasConcept C50644808 @default.
• W3216108926 hasConceptScore W3216108926C11413529 @default.
• W3216108926 hasConceptScore W3216108926C115903868 @default.
• W3216108926 hasConceptScore W3216108926C11731999 @default.
• W3216108926 hasConceptScore W3216108926C119857082 @default.
• W3216108926 hasConceptScore W3216108926C127413603 @default.
• W3216108926 hasConceptScore W3216108926C133731056 @default.
• W3216108926 hasConceptScore W3216108926C136389625 @default.
• W3216108926 hasConceptScore W3216108926C153180895 @default.
• W3216108926 hasConceptScore W3216108926C153258448 @default.
• W3216108926 hasConceptScore W3216108926C154945302 @default.
• W3216108926 hasConceptScore W3216108926C177264268 @default.
• W3216108926 hasConceptScore W3216108926C199360897 @default.
• W3216108926 hasConceptScore W3216108926C2779127903 @default.
• W3216108926 hasConceptScore W3216108926C2781390188 @default.
• W3216108926 hasConceptScore W3216108926C38858127 @default.
• W3216108926 hasConceptScore W3216108926C41008148 @default.
• W3216108926 hasConceptScore W3216108926C50644808 @default.
• W3216108926 hasFunder F4320321001 @default.
• W3216108926 hasLocation W32161089261 @default.
• W3216108926 hasLocation W32161089262 @default.

• next