Entropy estimation in bidimensional sequences

التفاصيل البيبلوغرافية
العنوان: Entropy estimation in bidimensional sequences
المؤلفون: Filho, F. N. M. de Sousa, de Sá, V. G. Pereira, Brigatti, E.
المصدر: Physical Review E 105, 054116 (2022)
سنة النشر: 2022
المجموعة: Condensed Matter
Physics (Other)
مصطلحات موضوعية: Physics - Data Analysis, Statistics and Probability, Condensed Matter - Statistical Mechanics
الوصف: We investigate the performance of entropy estimation methods, based either on block entropies or compression approaches, in the case of bidimensional sequences. We introduce a validation dataset made of images produced by a large number of different natural systems, in the vast majority characterized by long-range correlations, which produce a large spectrum of entropies. Results show that the framework based on lossless compressors applied to the one-dimensional projection of the considered dataset leads to poor estimates. This is because higher-dimensional correlations are lost in the projection operation. The adoption of compression methods which do not introduce dimensionality reduction improves the performance of this approach. By far, the best estimation of the asymptotic entropy is generated by the faster convergence of the traditional block-entropies method. As a by-product of our analysis, we show how a specific compressor method can be used as a potentially interesting technique for automatic detection of symmetries in textures and images.
Comment: 10 pages, 7 figures
نوع الوثيقة: Working Paper
DOI: 10.1103/PhysRevE.105.054116
URL الوصول: http://arxiv.org/abs/2207.02672
رقم الأكسشن: edsarx.2207.02672
قاعدة البيانات: arXiv
الوصف
DOI:10.1103/PhysRevE.105.054116