Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...
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...
- This paper presents a simulation tool targeted specifically at bang-bang type phase locked loop systems. The aim of this simulator is to quickly and accurately predict important ...
Previous work discussed a model of cognitive distance with the novel concepts of "tech bias", "velocity" and "inertia". This paper examines the human...
Christiaan A. D'H Gough, Richard Green, Mark Billi...
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...