id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_cocjcgde7vgvpbfuwmkltp7vky	Hananel Hazan	Topological constraints and robustness in liquid state machines	2012	10	.pdf	application/pdf	8180	773	65	The Liquid State Machine (LSM) is a method of computing with temporal neurons, which can be used pattern of all the neurons which feed-back in a sufficiently recurrent and inter-connected network. Twenty percentage uniform random connectivity with memory input to the detector. Twenty percentage uniform random connectivity with memory input to the detector. Twenty percentage uniform random connectivity with memory input to the detector. Twenty percentage uniform random connectivity with memory input to the detector. Twenty percentage uniform random connectivity with memory input to the detector. input, different amounts of ''dead'' neuron damage, average connectivity of 20% input, different amounts of ''noise generator'' neuron damage, average connectivity Histographs of correctness results in LSM networks with one hub distribution with different amounts of ''noise generator'' neuron damage. The architecture of the neural network detector was 204 input neurons (which were never taken from the neurons in the LSM	./cache/work_cocjcgde7vgvpbfuwmkltp7vky.pdf	./txt/work_cocjcgde7vgvpbfuwmkltp7vky.txt