Complexity and dynamic characteristics of a new discrete-time hyperchaotic model

被引：0

作者：

Natiq, Hayder ^{[1
]}

Al-Saidi, Nadia. M. G. ^{[2
]}

Said, M. R. M. ^{[1
]}

机构：

[1] Univ Putra Malaysia, Inst Math Res, Serdang, Malaysia

[2] Univ Technol Baghdad, Dept Appl Sci, Baghdad, Iraq

来源：

2017 SECOND AL-SADIQ INTERNATIONAL CONFERENCE ON MULTIDISCIPLINARY IN IT AND COMMUNICATION SCIENCE AND APPLICATIONS (AIC-MITCSA) | 2017年

关键词：

Hyperchaotic; Lyapunov exponents; Approximate entropy; Complexity analysis; APPROXIMATE ENTROPY;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Based on two of the existing one-dimensional chaotic maps and the two-dimensional H ' enon map, a new two-dimensional Henon-Gaussian-Sine model (2D-HGSM) is proposed. Basic dynamic characteristics of the 2D-HGSM are studied from the following three aspects: trajectory, bifurcation diagram and Lyapunov exponents. The complexity of 2D-HGSM is investigated by means of Approximate entropy. Performance evaluations show that the 2D-HGSM has higher complexity level, better ergodicity, wider chaotic and hyperchaotic region than different chaotic maps. Furthermore, the 2D-HGSM exhibits a qualitatively different chaotic behavior with respect to the variation of its corresponding parameters. Therefore, the 2D-HGSM has good application prospects in secure communication.

引用

页码：1 / 6

页数：6

共 50 条

[31] Discrete-time dynamic water quality index model in coastal water
Hapoglu, H.
Camcioglu, S.
Ozyurt, B.
Yildirim, P.
Balas, L.
GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM, 2021, 7 (02): : 197 - 210
[32] DECENTRALIZED ADAPTIVE SYNCHRONIZATION OF A STOCHASTIC DISCRETE-TIME MULTIAGENT DYNAMIC MODEL
Ma, Hong-Bin
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2009, 48 (02) : 859 - 880
[33] An explicit discrete-time dynamic vehicle model with assured numerical stability
Zhan, Guojian
Ge, Qiang
Gao, Haoyu
Yin, Yuming
Zhao, Bin
Eben Li, Shengbo
VEHICLE SYSTEM DYNAMICS, 2024,
[34] Decentralized Adaptive Synchronization of a Stochastic Discrete-Time Multiagent Dynamic Model
Ma, Hongbin
PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, : 2628 - 2633
[35] Analytical Solution to a Discrete-Time Model for Dynamic Learning and Decision Making
Zhang, Hao
MANAGEMENT SCIENCE, 2022, 68 (08) : 5924 - 5957
[36] On secure communication scheme-based mixed discrete-time hyperchaotic systems
Khalifa, Narjes
Benrejeb, Mohamed
JOURNAL OF DIFFERENCE EQUATIONS AND APPLICATIONS, 2023, 29 (9-12) : 1429 - 1448
[37] Encrypted Audio Communication Design using Synchronized Discrete-Time Hyperchaotic Maps
Hammami, Sonia
Djemai, Mohamed
Busawon, Krishna
2016 10TH INTERNATIONAL SYMPOSIUM ON COMMUNICATION SYSTEMS, NETWORKS AND DIGITAL SIGNAL PROCESSING (CSNDSP), 2016,
[38] NEW APPROACH TO DIFFERENTIAL DYNAMIC-PROGRAMMING FOR DISCRETE-TIME SYSTEMS
OHNO, K
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1978, 23 (01) : 37 - 46
[39] A New Discrete-Time Model for Channels Impaired by Phase Noise
Piemontese, Amina
Colavolpe, Giulio
Eriksson, Thomas
2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2021,
[40] Discrete-time dynamic user-optimal departure time route choice model
Chen, HK
Hsueh, CF
JOURNAL OF TRANSPORTATION ENGINEERING-ASCE, 1998, 124 (03): : 246 - 254

← 1 2 3 4 5 →