1 research outputs found
Computing threshold functions using dendrites
Neurons, modeled as linear threshold unit (LTU), can in theory compute all
thresh- old functions. In practice, however, some of these functions require
synaptic weights of arbitrary large precision. We show here that dendrites can
alleviate this requirement. We introduce here the non-Linear Threshold Unit
(nLTU) that integrates synaptic input sub-linearly within distinct subunits to
take into account local saturation in dendrites. We systematically search
parameter space of the nTLU and TLU to compare them. Firstly, this shows that
the nLTU can compute all threshold functions with smaller precision weights
than the LTU. Secondly, we show that a nLTU can compute significantly more
functions than a LTU when an input can only make a single synapse. This work
paves the way for a new generation of network made of nLTU with binary
synapses.Comment: 5 pages 3 figure