Apparatus and methods for salient feature detection by a spiking neuron network. The
network may comprise feature-specific units capable of responding to different objects (red …

Аннотация Дан обзор основных идей нейросетевого моделирования когнитивных
функций мозга. Описан ряд моделей нейрона (пороговый нейрон Мак‑Каллока и …

The main contribution of this letter is the derivation of a steepest gradient descent learning
rule for a multilayer network of theta neurons, a one-dimensional nonlinear neuron model …

This paper concerns the development of a prototype of a six-legged robot for space
exploration. The robot is a testbed for a new control technique based on a peculiar kind of …

We evolve spiking neural networks that implement a seek-push-release drive for a simple
simulated agent interacting with objects. The evolved agents display minimally-cognitive …

To understand how biological and bio-inspired complex computational networks can
function in the presence of noise and damage, we have evolved very small spiking neural …

Most sensory stimuli are temporal in structure. How action potentials encode the information
incoming from sensory stimuli remains one of the central research questions in …

Neuroevolution comprehends the class of methods responsible for evolving neural network
topologies and weights by means of evolutionary algorithms. Despite their good …

We evolve both topology and synaptic weights of recurrent very small spiking neural
networks in the presence of noise on the membrane potential. The noise is at a level similar …

Biological and artificial spiking neural networks process information by changing their states
in response to the temporal patterns of input and of the activity of the network itself. Here we …