Abstract
Abstract Separation ability is one of two most important properties of Liquid State Machines used in the Liquid Computing theory. To measure the so-called distance of states that Liquid State Machine can exist in – different norms and metrics can be applied. Till now we have used the Euclidean distance to tell the distance of states representing different stimulations of simulated cortical microcircuits. In this paper we compare our previously used methods and the approach with Bray-Curtis measure of dissimilarity. Systematic analysis of efficiency and its comparison for a different number of simulated synapses present in the model will be discussed to some extent.
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