Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
Abstract. A coarse-coding regulatory model that facilitates neural heterogeneity through a morphogenetic process is presented. The model demonstrates cellular and tissue extensibil...
Jekanthan Thangavelautham, Gabriele M. T. D'Eleute...
This paper presents a class of neural networks suitable for the application of decoding error-correcting codes.The neural model is basically a perceptron with a high-order polynom...
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
Silvia Ferrari, Bhavesh Mehta, Gianluca Di Muro, A...
We propose a novel application of Formal Concept Analysis (FCA) to neural decoding: instead of just trying to figure out which stimulus was presented, we demonstrate how to explor...