This paper presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces (RKHS). Unlike previous approaches that exploit the kernel trick on filtered ...
Devis Tuia, Gustavo Camps-Valls, Manel Martí...
Simplification of mixture models has recently emerged as an important issue in the field of statistical learning. The heavy computational demands of using large order models dro...
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
Compressive sensing and processing delivers high resolution data using reduced sampling rates and computational effort compared to Nyquist sensing and processing. Compressive proc...
In this paper, we consider improvement of parameter estimation accuracy of multicomponent polynomial-phase signals (mc-PPSs) using the product high-order ambiguity function (PHAF)...