A method of topological grammars is proposed for multidimensional data approximation. For data with complex topology we define a principal cubic complex of low dimension and give...
Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zi...
The ability to detect weak distributed activation patterns in networks is critical to several applications, such as identifying the onset of anomalous activity or incipient conges...
Aarti Singh, Robert D. Nowak, A. Robert Calderbank
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
In Image Compression, the researchers' aim is to reduce the number of bits required to represent an image by removing the spatial and spectral redundancies. Recently discrete...
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...