Entropy

About the journal

Entropy deals with the development and/or application of entropy or information-theoretic concepts in a wide variety of applications. Relevant submissions ought to focus on one of the following:* develop the theory behind entropy or information theory* provide new insights into entropy or information-theoretic concepts* demonstrate a novel use of entropy or information-theoretic concepts in an application* obtain new results using concepts of entropy or information theory

Articles

• Milton Silva, Diogo Pratas, Armando J. Pinho. AC2: An Efficient Protein Sequence Compression Tool Using Artificial Neural Networks and Cache-Hash Models. Entropy, vol. 23, no. 5, p. 530, April 2021
• Jorge Miguel Silva, Eduardo Pinho, Sérgio Matos, Diogo Pratas. Statistical Complexity Analysis of Turing Machine Tapes with Fixed Algorithmic Complexity Using the Best-Order Markov Model. Entropy, vol. 22, no. 1, January 2020
• Diogo Pratas, Morteza Hosseini, Jorge Miguel Silva, Armando J. Pinho. A reference-free lossless compression algorithm for DNA sequences using a competitive prediction of two classes of weighted models. Entropy, vol. 21, p. 1074, November 2019
• Diogo Pratas, Raquel Silva, Armando J. Pinho. Comparison of Compression-Based Measures with Application to the Evolution of Primate Genomes. Entropy, vol. 20, no. 6, p. 393, May 2018
• Manuel J. Duarte, Armando J. Pinho. Bacterial DNA sequence compression models using artificial neural networks. Entropy, vol. 15, p. 3435-3448, August 2013

Impact factor

The impact factor of Entropy is as follows: