Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area coordinating neurocont...
Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Har...
Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability,...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
This paper presents a new development of the NeuroVaria method. NeuroVaria computes relevant atmospheric and oceanic parameters by minimizing the difference between the observed s...
—In this paper, a neural network solution to extract independent components from nonlinearly mixed signals is proposed. Firstly, a structurally constrained mixing model is introd...
Pei Gao, Li Chin Khor, Wai Lok Woo, Satnam Singh D...