For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Hierarchical modularity is a familiar characteristic of a large class of natural dynamical systems. A normal interpretation of modularity is that interactions between subsystems a...
To manage the complicated data such as recursive elements, multiply namespaces, repeatable structures, extended elements and attributes in the XML Binding documents of distance ed...
Learning dominant motion patterns or activities from a video is an important surveillance problem, especially in crowded environments like markets, subways etc., where tracking of...