- This paper presents a variable node-to-node-link neural network (VN2 NN) trained by real-coded genetic algorithm (RCGA). The VN2 NN exhibits a node-to-node relationship in the hi...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
— Neural networks are used in a wide number of fields including signal and image processing, modeling and control and pattern recognition. Some of the most common type of neural ...
Raveesh Kiran, Sandhya R. Jetti, Ganesh K. Venayag...
A key to overcoming the limitations of classical artificial intelligence and to deal well with enormous amounts of information might be brain-like computing in which distributed re...
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...