2 papers
cs.NE2015
An Approximate Backpropagation Learning Rule for Memristor Based Neural Networks Using Synaptic Plasticity
D. V. Negrov, I. M. Karandashev, V. V. Shakirov +3
We describe an approximation to backpropagation algorithm for training deep neural networks, which is designed to work with synapses implemented with memristors. The key idea is to…
q-bio.NC2015
Models of Innate Neural Attractors and Their Applications for Neural Information Processing
Ksenia P. Solovyeva, Iakov M. Karandashev, Alex Zhavoronkov +1
In this work we reveal and explore a new class of attractor neural networks, based on inborn connections provided by model molecular markers, the molecular marker based attractor n…