Least-Squares Fuzzy Transforms and Autoencoders: Some Remarks and Application

Abstract

In this article, analogies and differences between a type of fuzzy transform and a type of autoencoder, both based on a least-squares optimization, will be discussed. Such schemes have been recently introduced in the literature in different contexts. In particular, in this article, the data compression application will be considered. As it will be shown, the least-squares fuzzy transform can be regarded as a kind of autoencoder with a lower computational cost, without losing accuracy. The numerical comparison against existing results for the considered application shows the good performance of the fuzzy transform based approach.