To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
A novel STAP algorithm based on sparse recovery technique, called CS-STAP, were presented. Instead of using conventional maximum likelihood estimation of covariance matrix, our met...
Ke Sun, Hao Zhang, Gang Li, Huadong Meng, Xiqin Wa...
We tackle the challenging problem of mining the simplest Boolean patterns from categorical datasets. Instead of complete enumeration, which is typically infeasible for this class ...
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiï¬...
Abstract--This paper presents a dynamic predictiveoptimization framework of a nonlinear temporal process. Datamining (DM) and evolutionary strategy algorithms are integrated in the...