Artificial grammar recognition using spiking neural networks
Petersson Karl, Çürüklü Baran, Cavaco Philip
BMC Neuroscience · 2009
doi:10.1186/1471-2202-10-s1-p352 (opens in a new tab)
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Abstract
A biologically inspired neocortical model consisting of spiking neurons is designed to perform artificial grammar processing. Building on work in [ 1 ], the model is designed to categorize symbol strings as belonging to a Reber grammar [ 2 ]. Columnar organization of the cortex is used as the general inspiration of the network [ 3 , 4 ].
Abstract licence: CC BY-NC-ND
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