High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
The Internet’s core routing infrastructure, while arguably robust and efficient, has proven to be difficult to evolve to accommodate the needs of new applications. Prior researc...
Boon Thau Loo, Joseph M. Hellerstein, Ion Stoica, ...
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
Abstract—Despite the considerable amount of research work on the application of Gabor filters in pattern classification, their design and selection have been mostly done on a t...