Standard detection algorithms for nonlinearity linkage fail when applied to typical problems in the analysis of financial time-series data. We explain how this failure arises whe...
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
In recent literature, the niche enabling effects of crowding and the sharing algorithms have been systematically investigated in the context of Genetic Algorithms and are now estab...
A system for the tracking and classification of livestock movements is presented. The combined `tracker-classifier' scheme is based on a variant of Isard and Blakes `Condensa...
This paper presents an automated analog synthesis tool for topology generation and subsequent circuit sizing. Though sizing is indispensable, the paper mainly concentrates on topo...