@inproceedings{1a49ac917d8e4edd8f94692755d33a77,
title = "Construction of Piecewise Chaotic Maps With Tunable Statistical Mean",
abstract = "In numerous chaos based applications, it is often important to use chaotic maps that showcase desirable statistical characteristics, that can improve the performance of the designed architecture. Yet, it is hard to design maps that can achieve the desired statistical properties. Motivated by this, this work considers a family of piecewise chaotic maps, and studies how tuning their parameters can affect the mean value of the generated chaotic trajectories. Such a family of maps can be highly practical in future chaos based applications.",
keywords = "Chaos, encryption, mean value, optimization, piecewise map",
author = "Lazaros Moysis and Marcin Lawnik and Baptista, \{Murilo S.\} and Sotirios Goudos and Christos Volos",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023 ; Conference date: 28-06-2023 Through 30-06-2023",
year = "2023",
doi = "10.1109/MOCAST57943.2023.10176612",
language = "English",
series = "2023 12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023 - Proceedings",
address = "United States",
}