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Author/Affiliation: Mounir Boukadoum
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Open AccessArticle
14 Pages, 5,442 KB Download PDF
Neural Synchrony-Based State Representation in Liquid State Machines, an Exploratory Study

by Nicolas Pajot and Mounir Boukadoum
Journal of Engineering Research and Sciences, Volume 2, Issue 11, Page # 1-14, 2023; DOI: 10.55708/js0211001
Abstract: Solving classification problems by Liquid State Machines (LSM) usually ignores the influence of the liquid state representation on performance, leaving the role to the reader circuit. In most studies, the decoding of the internally generated neural states is performed on spike rate-based vector representations. This approach occults the interspike timing, a central aspect of biological… Read More

(This article belongs to the Special Issue on SP4 (Special Issue on Computing, Engineering and Sciences 2023-24) and the Section Neurosciences (NES))

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