现代战争中,跨平台武器单元的协同利用,是合同编队体系的重要内容,作战方式也正由平台级协同向着能力要素级协同转变,这对武器目标分配问题的解决提出了更大挑战。本文将武器单元的最小划分单位细化到能力要素级,以毁伤概率与成本消耗...现代战争中,跨平台武器单元的协同利用,是合同编队体系的重要内容,作战方式也正由平台级协同向着能力要素级协同转变,这对武器目标分配问题的解决提出了更大挑战。本文将武器单元的最小划分单位细化到能力要素级,以毁伤概率与成本消耗为优化目标,面向多种来袭目标的编队防空场景,提出了跨平台武器目标分配算法。同时,基于混沌映射提出了混沌种群重构(chaotic population reconstruction,CPR)机制,并结合带存档的自适应差分进化(adaptive differential evolution with optional external archive,JADE)算法提出了CPR-JADE算法,利用CPR机制可以帮助算法在解决高维复杂约束问题时跳出局部最优。再将其运用到武器目标分配模型上,实现了对模型的高效求解。最后,通过在多种数据规模下与其他进化优化算法的仿真对比试验分析,验证了所提方法的正确性与有效性。展开更多
Chaotic cryptography has been applied to image encryption;however,only the traditional low-dimensional chaotic systems has been widely analyzed or deciphered,which does not show satisfied security and efficiency.To so...Chaotic cryptography has been applied to image encryption;however,only the traditional low-dimensional chaotic systems has been widely analyzed or deciphered,which does not show satisfied security and efficiency.To solve this problem,a new algorithm based on cross-chaos map has been created in this article.The image pixels are scrambled under control of high-dimensional chaotic sequence,which is generated by cross chaotic map.The image pixels are substituted by ciphertext feedback algorithm.It can relate encryption required parameters with plaintext and can make a plaintext byte affect more ciphertext bytes.Proved by theoretical analysis and experimental results,the algorithm has higher complex degree and has passed SP800-22 pseudo-random number standard tests,and it has high encryption speed,high security,etc.It can be widely applied in the field of image encryption.展开更多
为了保证数字温度传感器对温度的准确读取,需要对传感器温度误差展开有效控制。为了提高数字温度传感器温度误差控制效果,提出基于混沌误差反向传播(Error Back Propagation Training,BP)神经网络算法的数字温度传感器温度误差模糊控制...为了保证数字温度传感器对温度的准确读取,需要对传感器温度误差展开有效控制。为了提高数字温度传感器温度误差控制效果,提出基于混沌误差反向传播(Error Back Propagation Training,BP)神经网络算法的数字温度传感器温度误差模糊控制方法。首先利用经验模态分解法对收集到的温度测量数据展开去噪处理,计算不同温度区间内的温度测量超差概率,进而实现误差特征阈值的提取;建立三层神经网络,通过对温度误差的反复训练达到温度补偿目的。引入Logistic映射法与混沌扩频序列法,计算混沌系数间的互协方差函数,采用M-N-L结构的前馈网络对原BP网络的三层建构展开优化,并以此提高温度误差模糊控制的精度。测试结果表明:方法对传感器温度误差的提取值与实际超差值的差距低于0.03,收敛步数小于120步,误差补偿后误差比率低于19.3%,残差平方和低于0.23,对传感器温度误差的控制更加精准,温度补偿的效率更高,提高了误差控制效果。展开更多
In order to achieve image encryption and data embedding simultaneously, a reversible data hiding(RDH) algorithm for encrypted-compressed image in wavelet domain is proposed. This scheme employs the quality controllabl...In order to achieve image encryption and data embedding simultaneously, a reversible data hiding(RDH) algorithm for encrypted-compressed image in wavelet domain is proposed. This scheme employs the quality controllable parameter. Moreover it has larger embedding capacity and smaller quality control parameters than other methods in literatures. Meanwhile, the cross chaotic map is employed to generate chaotic sequences, and the total keys of the algorithm is far large. Experimental results and comparisons show that the proposed scheme has large capacity, high security, and strong resistance to brute-force.展开更多
文摘现代战争中,跨平台武器单元的协同利用,是合同编队体系的重要内容,作战方式也正由平台级协同向着能力要素级协同转变,这对武器目标分配问题的解决提出了更大挑战。本文将武器单元的最小划分单位细化到能力要素级,以毁伤概率与成本消耗为优化目标,面向多种来袭目标的编队防空场景,提出了跨平台武器目标分配算法。同时,基于混沌映射提出了混沌种群重构(chaotic population reconstruction,CPR)机制,并结合带存档的自适应差分进化(adaptive differential evolution with optional external archive,JADE)算法提出了CPR-JADE算法,利用CPR机制可以帮助算法在解决高维复杂约束问题时跳出局部最优。再将其运用到武器目标分配模型上,实现了对模型的高效求解。最后,通过在多种数据规模下与其他进化优化算法的仿真对比试验分析,验证了所提方法的正确性与有效性。
基金Supported by the National Natural Science Foundation of China (60973162)the Natural Science Foundation of Shandong Province of China (ZR2009GM037)+2 种基金the Science and Technology Project of Shandong Province,China (2010GGX10132,2012GGX10110)the Key Natural Science Foundation of Shan-dong Province of China (Z2006G01)the Soft Science Project of Shangdong Province of China (2012RKA10009)
文摘Chaotic cryptography has been applied to image encryption;however,only the traditional low-dimensional chaotic systems has been widely analyzed or deciphered,which does not show satisfied security and efficiency.To solve this problem,a new algorithm based on cross-chaos map has been created in this article.The image pixels are scrambled under control of high-dimensional chaotic sequence,which is generated by cross chaotic map.The image pixels are substituted by ciphertext feedback algorithm.It can relate encryption required parameters with plaintext and can make a plaintext byte affect more ciphertext bytes.Proved by theoretical analysis and experimental results,the algorithm has higher complex degree and has passed SP800-22 pseudo-random number standard tests,and it has high encryption speed,high security,etc.It can be widely applied in the field of image encryption.
文摘为了保证数字温度传感器对温度的准确读取,需要对传感器温度误差展开有效控制。为了提高数字温度传感器温度误差控制效果,提出基于混沌误差反向传播(Error Back Propagation Training,BP)神经网络算法的数字温度传感器温度误差模糊控制方法。首先利用经验模态分解法对收集到的温度测量数据展开去噪处理,计算不同温度区间内的温度测量超差概率,进而实现误差特征阈值的提取;建立三层神经网络,通过对温度误差的反复训练达到温度补偿目的。引入Logistic映射法与混沌扩频序列法,计算混沌系数间的互协方差函数,采用M-N-L结构的前馈网络对原BP网络的三层建构展开优化,并以此提高温度误差模糊控制的精度。测试结果表明:方法对传感器温度误差的提取值与实际超差值的差距低于0.03,收敛步数小于120步,误差补偿后误差比率低于19.3%,残差平方和低于0.23,对传感器温度误差的控制更加精准,温度补偿的效率更高,提高了误差控制效果。
基金Supported by the Chongqing Research Program of Basic Research and Frontier Technology(cstc2017jcyjBX0008)the Graduate Student Research and Innovation Foundation of Chongqing(CYB17026)the Basic Applied Research Program of Qinghai Province(2019-ZJ-7099)
文摘In order to achieve image encryption and data embedding simultaneously, a reversible data hiding(RDH) algorithm for encrypted-compressed image in wavelet domain is proposed. This scheme employs the quality controllable parameter. Moreover it has larger embedding capacity and smaller quality control parameters than other methods in literatures. Meanwhile, the cross chaotic map is employed to generate chaotic sequences, and the total keys of the algorithm is far large. Experimental results and comparisons show that the proposed scheme has large capacity, high security, and strong resistance to brute-force.
