Cosine-transform-based chaotic system for image encryption

In this paper, a SEIR epidemic model for the COVID-19 is built according to some general control strategies, such as hospital, quarantine and external input Based on the data of Hubei province, the particle swarm optimization (PSO) algorithm is applied to estimate the parameters of the system We found that the parameters of the proposed SEIR model are different for different scenarios Then, the model is employed to show the evolution of the epidemic in Hubei province, which shows that it can be used to forecast COVID-19 epidemic situation Moreover, by introducing the seasonality and stochastic infection the parameters, nonlinear dynamics including chaos are found in the system Finally, we discussed the control strategies of the COVID-19 based on the structure and parameters of the proposed model

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SEIR modeling of the COVID-19 and its dynamics.

2D Logistic-Sine-coupling map for image encryption

A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation

Fast image encryption algorithm based on parallel computing system

A fast image encryption algorithm based on chaotic map

A fast image encryption algorithm based on compressive sensing and hyperchaotic map

An effective image encryption algorithm based on compressive sensing and 2D-SLIM

To determine whether a given deterministic nonlinear dynamic system is chaotic or periodic, a novel test approach named zero-one (0-1) test has been proposed recently. In this approach, the regular and chaotic motions can be decided by calculating the parameter K approaching asymptotically to zero or one. In this study, we focus on the 0-1 test algorithm and illustrate the selection of parameters of this algorithm by numerical experiments. To validate the reliability and the universality of this algorithm, it is applied to typical nonlinear dynamic systems, including fractional-order dynamic system.

The 0-1 test algorithm for chaos and its applications

The complexities of multi-wing chaotic systems based on the modified Chen system and a multi-segment quadratic function are investigated by employing the statistical complexity measure (SCM) and the spectral entropy (SE) algorithm. How to choose the parameters of the SCM and SE algorithms is discussed. The results show that the complexity of the multi-wing chaotic system does not increase as the number of wings increases, and it is consistent with the results of the Grassberger—Procaccia (GP) algorithm and the largest Lyapunov exponent (LLE) of the multi-wing chaotic system.

http://or.nsfc.gov.cn/bitstream/00001903-5/94432/1/1000005475090.pdf

Congxu Zhu

Papers

A fast image encryption algorithm based on chaotic map

A fast image encryption algorithm based on compressive sensing and hyperchaotic map

An effective image encryption algorithm based on compressive sensing and 2D-SLIM

The 0-1 test algorithm for chaos and its applications

Complexity analyses of multi-wing chaotic systems