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Dual chaotic encryption method for wireless communication privacy data based on deep learning. [PDF]
Yu H.
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Some New Maximally Chaotic Discrete Maps. [PDF]
Choi H +5 more
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Secure color image encryption using a fractional-order chaotic PRNG and DNA-level operations. [PDF]
Yang C, Liu Y, Sun X, Han Q, Zhou D.
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Differentiation of Benign and Malignant BI-RADS 4-5 Breast Lesions Using Ultrasound Localization Microscopy-Derived Microvascular Biomarkers: A Prospective Study. [PDF]
Wei W +8 more
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Chaotic Lévy flight Grey wolf optimizer for optimal design and techno-economic assessment of grid-connected solar photovoltaic power plant in Assam. [PDF]
Devi RM +3 more
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Designing 1D Chaotic Maps for Fast Chaotic Image Encryption
Chaotic maps that can provide highly secure key sequences and ease of structure implementation are predominant requirements in image encryption systems.
Mustafa Kamil Khairullah +2 more
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CONSTRUCTING CHAOTIC POLYNOMIAL MAPS
International Journal of Bifurcation and Chaos, 2009This paper studies the construction of one-dimensional real chaotic polynomial maps. Given an arbitrary nonzero polynomial of degree m (≥ 0), two methods are derived for constructing chaotic polynomial maps of degree m + 2 by simply multiplying the given polynomial with suitably designed quadratic polynomials.
Xu Zhang 0005, Yuming Shi, Guanrong Chen
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CHAOTIC CONTROL OF LOGISTIC MAP
Modern Physics Letters B, 2008With the occasional feedback method, the chaotic logistic map is stabilized at an unstable low-periodic orbit. In our method, the qualified feedback coefficient can be obtained through calculation instead of through simulation. Besides, the bifurcation control of the logistic map is studied, and a new scheme is proposed to change the parameter value of
Wang, Xingyuan, Wang, Mingjun
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2007
The parametrically coupled map lattice (PCML) exhibits many interesting dynamical behaviors that are reminiscent of the adaptation and the learning of the neural network. In order for the PCML to be a model of the neural network, however, it is necessary to identify the biological counterpart of one-dimensional maps that constitute the PCML. One of the
Lee, G Lee, Geehyuk, Yi, GS Yi, Gwan-Su
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The parametrically coupled map lattice (PCML) exhibits many interesting dynamical behaviors that are reminiscent of the adaptation and the learning of the neural network. In order for the PCML to be a model of the neural network, however, it is necessary to identify the biological counterpart of one-dimensional maps that constitute the PCML. One of the
Lee, G Lee, Geehyuk, Yi, GS Yi, Gwan-Su
openaire +1 more source

