— Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process s...
—This paper examines the motivation and concepts of dynamic encoders (for binary neural networks) introduced by Shah in the author’s RASC 2004 and 2006 conference papers [1], [...
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
- 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...