基于混沌技术的蚁群混合优化方法

为提高蚁群优化算法的求解性能,在分析了处理连续变量的蚁群优化算法的基础上,给出了两种混沌映射的映射规则,并构建了基于Logistic映射的混沌蚁群优化方法（LM-ACO）以及基于Henon映射的混沌蚁群优化方法（HM-ACO）,给出了[k]次均方根包络函数简化及平滑多约束条件的处理方法。采用LM-ACO、HM-ACO以及蚁群处理连续变量的优化方法分别对机械有约束优化实例进行求解,在求解过程中,从各种方法获得的最优解、成功率指标、平均有效迭代数、迭代占用时间等方面作对比。比较结果表明：采用基于Henon映射的蚁群混合优化方法具有求解精度高、优化效率高等优点。     

基于混沌映射的网络实时保密通信方法

本文就混沌系统中的Logistic映射和Henon映射,利用多值序列的方法所产生的混沌序列,对网络流进行加密和置乱,并对数字图像也进行了实验,算法全部用VC 编写实现。     

一种基于Logistic映射的数字图像迭代混沌加密方法

介绍混沌加密原理、方法及安全性分析。     

二维Logistic映射中混沌与分形的研究

研究了二维Ｌｏｇｉｓｔｉｃ映射非线性动态行为的普适特征后发现,控制参数不同,二维Ｌｏｇｉｓｔｉｃ映射可分别按Ｆｅｉｇｅｎｂａｕｍ途径、Ｒｕｂｅｌｌｅ－Ｔａｋｅｎｓ－Ｎｅｗｈｏｕｓｅ方案和Ｐｏｍｅａｕ－Ｍａｎｎｅｖｉｌｌｅ途径走向混沌,且在控制参数空间中的较大区域,其通向混沌的道路与Ｈｏｐｆ分岔有关,在这些途径上可观察到锁相和准周期运动。同时对二维Ｌｏｇｉｓｔｉｃ映射的分形研究表明,控制参数不同,分     

一种基于混沌密钥的VEA加密算法设计

本文提出了一种基于混沌密钥的VEA加密算法设计,即通过Logistic混沌系统方程,产生加密的二进制密钥流序列,与图像DCT转换后的DCT系数进行加密,得到加密图像。通过使用混沌密钥进行加密的视频数据,具有安全性高、抵抗攻击能力强等特点。     

一种混沌理论下的需求演化模型

需求的不确定性和易变性一直是影响软件生命周期,困扰软件开发效率和开发质量的重要因素。通过对动力系统和软件复杂性理论的研究,提出了一种混沌演化模型,该模型可以对软件需求的演化过程进行指导,同时也可以评价需求过程的质量。研究表明,只要需求演化过程的变化图和模型的轨迹图一致,那么需求的演化过程就可以看成是正常的。通过对具体实例的分析,进一步说明了该模型在评价需求演化过程上是有效可行的。     

基于混沌优化的非线性预测控制器

针对非线性系统的控制问题,本文将神经网络辨识、混沌优化和预测控制思想有机结合,提出了一种新型非线性预测控制器.该控制器以神经网络作为预测模型,混沌优化算法作为滚动优化策略,避免了非线性预测控制中复杂的梯度计算和矩阵求逆问题.另外在训练神经网络过程中,采用了带混沌机制的自适应学习率的BP算法,以提高神经网络的收敛能力和收敛速度.仿真研究说明了该非线性预测控制器的有效性及实时性.     

一种基于双混沌映射的加密算法设计与应用*

提出了一种基于logistic和Henon的双混沌映射加密算法,通过级联一维混沌系统和二维混沌系统,利用复合迭代所产生的混沌序列对明文进行加密,开发了算法的模拟实验平台。实验结果表明,与传统DES和基于Lorenz的加密相比,该算法在加密强度和运算效率上达到了较好的均衡。     

一种新的基于时空混沌的伪随机数发生器

时空混沌系统有很好的密码学特性,常被用来设计伪随机数发生器。然而,时空混沌系统的概率密度分布不均匀,不利于保证伪随机数发生器的安全。针对此问题,提出一种新的基于时空混沌系统的伪随机发生器算法。该算法从提升时空混沌局部映射的密码学性能入手,将分段Logistic映射作为局部映射,并通过改变时空混沌系统的耦合参数来解决概率密度分布不均的问题。理论分析与仿真实验的结果表明,该算法产生的序列具有良好的初值敏感性和随机性,同时具有良好的执行效率,能够满足信息加密安全的需要。     

基于双混沌和延迟Fibonacci数列的加密算法

提出基于双混沌和延迟Fibonacci数列的手机加密算法,算法以一维Logistic映射作为混沌模型,采用双混沌系统增加控制参数,使混沌行为更加复杂;利用延迟Fibonacci数列对混沌进行扰动处理,使融合后的序列更具有随机的特征;将明文参与到加密算法中,给密文生成带来不确定性,使局部攻击更加困难,在密码不变的场合更能...     

A new shock/discontinuity detector

A new effective shock/discontinuity detector has been developed in this work. The detector has two steps. The first step is to check the ratio of the truncation errors on the coarse and fine grids, and the second step is to check the local ratio of the left- and right-hand slopes. The currently popular shock/discontinuity detectors such as Harten's, Jameson's and WENO can detect shock, but mistake high-frequency waves and critical points as shock and then damp the physically important high-frequency waves. Preliminary results show that the new shock/discontinuity detector is very delicate and can detect all shocks including strong, weak and oblique shocks or discontinuity in function and first-, second- and third-order derivatives without artificial case-related constants, but never mistake high-frequency waves and critical points or expansion waves as shock. This will overcome the bottleneck problem with numerical simulation for the shock–boundary layer interaction, shock–acoustic interaction, image process, porous media flow, multiple phase flow, detonation wave, and anywhere the high-frequency waves are important, but discontinuity exists and is mixed with high-frequency waves. After detecting the shock, we can then use one-side high-order scheme for shocks and high-order central compact scheme for the smooth parts if the shock is appropriately located. Then a high-order universal subroutine for the finite difference method is developed, which can be used for any finite difference code for accurate numerical derivatives.     

双混沌机制优化方法及其应用

为了克服混沌优化方法在缩小优化变量的搜索空间前所进行的盲目搜索，提出一种具有双混沌机制的优化方法。该方法同时利用两种不同的混沌机制在搜索空间进行搜索，根据搜索情况来缩小搜索空间。该方法能够改善算法的通用性，避免了针对不同的优化函数选择搜索参数的缺点。仿真结果表明，该方法的搜索效率明显高于普通的混沌优化方法。     

Henon映射产生的地毯图案

由迭代函数系统可以产生地毯图案 ,这是由于迭代函数系统的随机性选择能产生分形图形。本文从不同的角度 ,利用确定的简单数学模型二维函数 Henon映射所特有的动力系统混沌性质生成了地毯图案。     

混沌同步的一些新结果

给出了混沌同步的一些新判据, 改进了当前文献的结果, 并提供了一些非常容易检验的关于混沌同步的代数条件.     

离散混沌系统类随机性的符号熵分析法

采用符号熵分析法,分析和讨论了经典的Logistic映射和Henon映射的类随机性强弱.先将离散混沌系统产生的实数序列转化为二进制序列,然后进行编码,计算其符号熵,绘制其符号熵图,并深入讨论了系统参数和初始值对符号熵的影响.数值仿真分析表明,符号熵法能定量区别不同离散混沌系统类随机性的强弱.同时作为随机源,Logistic映射比Henon映射好.     

混沌吸引子随机性的一种判别方法

在混沌科学领域,截至目前混沌吸引子随机性强弱还没有一个统一的评判标准,文章尝试提出了一种判别混沌随机性强弱的原理和算法,且该方法不需要相空间重构。应用该方法对周期运动、强弱混沌、两种离散混沌映射及噪声进行数值仿真,结果表明该方法能有效识别不同混沌运动的随机性强弱。     

A chaos based image encryption and lossless compression algorithm using hash table and Chinese Remainder Theorem

A chaos based image encryption and lossless compression algorithm using hash table and Chinese Remainder Theorem is proposed. Initially, the Henon map is used to generate the scrambled blocks of the input image. The scrambled block undergoes a fixed number of iterations based on the plain image using Arnold cat map. Since hyper chaos system has complex dynamical characteristics than chaos, the confused image is further permuted using the index sequence generated by the hyper chaos along with hash table structure. The permuted image is divided into blocks and the diffusion is carried out either by using Lorenz equations or by using another complex matrix generated from the plain image appropriately. Along with diffusion, compression is also carried out by Chinese Remainder Theorem for each block. This encryption algorithm has high key space, good NPCR and UACI values and very less correlation among adjacent pixels. Simulation results show the high effectiveness and security features of the proposed algorithm.     

A new adaptive mutative scale chaos optimization algorithm and its application

Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with finite collapses （e.g., Logistic map, Tent map, and Chebyshev map）, a new adaptive mutative scale chaos optimization algorithm （AMSCOA） is proposed by using the chaos model x = sin（2/x）. In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken： 1） the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2） the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.     

A new adaptive mutative scale chaos optimization algorithm and its application

Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin(2/x) with infinite collapses within the finite region[-1;1] to some representative iterative chaotic maps with finite collapses (e.g., Logistic map, Tent map, and Chebyshev map), a new adaptive mutative scale chaos optimization algorithm (AMSCOA) is proposed by using the chaos model x = in(2/x). In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken: 1) the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2) the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.     

一族由混沌所派生出来的图案

给出了一族由一个图形非常特别的混沌映射——网状映射以及Logistic映射与其它函数复合后生成的美术图案。所得结果对于舞台美术方面或其它与美术相关的领域有一定的实用价值。同时为分形的研究开辟了一个新的途径。为分形和混沌之间的联系找到了一个新的佐证。