With increasing demands for high performance by embedded systems, especially by digital signal processing applications, embedded processors must increase available instruction lev...
As an important technique for data analysis, clustering has been employed in many applications such as image segmentation, document clustering and vector quantization. Divisive cl...
Abstract. Several actions are usually performed when document is appended to textual database in information retrieval system. The most frequent actions are compression of the docu...
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
Abstract—Large-scale parallel applications often produce immense quantities of data that need to be analyzed. To avoid performing repeated, costly disk accesses, analysis of larg...