On linguistic variables and sparse representations

Abstract

Linguistic variables can be seen as dictionaries to represent data. In fields as Signal Processing or Machine Learning is usual to use or to search redundant dictionaries to promote sparse representations. This kind of representations present several interesting properties as a high generalization capacity, simplification and economy, among others. In this work, a revision of themainmethods to obtain sparse representations and their possible application to model with linguistic variables and Fuzzy Rule Systems is done.