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.

中文翻译：

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最小二乘模糊变换和自动编码器：一些评论和应用


在本文中，将讨论基于最小二乘优化的模糊变换类型和自动编码器类型之间的相似性和差异。最近在不同背景下的文献中引入了此类方案。特别是，在本文中，将考虑数据压缩应用程序。正如将要显示的，最小二乘模糊变换可以被视为一种计算成本较低且不损失精度的自动编码器。与所考虑的应用的现有结果的数值比较显示了基于模糊变换的方法的良好性能。