The temporal evolution of nearshore sandbars (alongshore ridges of sand fringing coasts in water depths less than 10 m and of paramount importance for coastal safety) is commonly ...
Leo Pape, B. Gerben Ruessink, Marco A. Wiering, Ia...
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Building on some prior work, in this paper we describe a novel structure termed the decoupled echo state network (DESN) involving the use of lateral inhibition. Two low-complexity...
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
Matthew H. Tong, Adam D. Bickett, Eric M. Christia...
We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We ...
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
In the antisaccade paradigm subjects are instructed to perform eye movements in the opposite direction from the location of a visually appearing stimulus while they are fixating ...
Vassilis Cutsuridis, Nikolaos Smyrnis, Ioannis Evd...
On the basis of detailed analysis of reaction times and neurophysiological data from tasks involving choice, it has been proposed that the brain implements an optimal statistical ...