Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
—In cognitive radio (CR) networks, licensed spectrum that can be shared by secondary users (SUs) is always restricted by the needs of primary users (PUs). Although channel aggreg...
—Spectrum sharing is an emerging mechanism to resolve the conflict between the spectrum scarcity and the growing demands for the wireless broadband access. In this paper we inve...
We propose a new ghost fluid approach for free surface and solid boundary conditions in Smoothed Particle Hydrodynamics (SPH) liquid simulations. Prior methods either suffer from...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...