In this study, we extend our previous adaptive steganographic algorithm to support point geometry. For the purpose of the vertex decimation process presented in the previous work, the neighboring information between p...In this study, we extend our previous adaptive steganographic algorithm to support point geometry. For the purpose of the vertex decimation process presented in the previous work, the neighboring information between points is necessary. Therefore, a nearest neighbors search scheme, considering the local complexity of the processing point, is used to determinate the neighbors for each point in a point geometry. With the constructed virtual connectivity, the secret message can be embedded successfully after the vertex decimation and data embedding processes. The experimental results show that the proposed algorithm can preserve the advantages of previous work, including higher estimation accuracy, high embedding capacity, acceptable model distortion, and robustness against similarity transformation attacks. Most importantly, this work is the first 3D steganographic algorithm for point geometry with adaptation.展开更多
For the unsorted database quantum search with the unknown fraction λ of target items, there are mainly two kinds of methods, i.e., fixed-point and trail-and-error.(i) In terms of the fixed-point method, Yoder et al. ...For the unsorted database quantum search with the unknown fraction λ of target items, there are mainly two kinds of methods, i.e., fixed-point and trail-and-error.(i) In terms of the fixed-point method, Yoder et al. [Phys. Rev. Lett.113 210501(2014)] claimed that the quadratic speedup over classical algorithms has been achieved. However, in this paper, we point out that this is not the case, because the query complexity of Yoder’s algorithm is actually in O(1/λ01/2)rather than O(1/λ1/2), where λ0 is a known lower bound of λ.(ii) In terms of the trail-and-error method, currently the algorithm without randomness has to take more than 1 times queries or iterations than the algorithm with randomly selected parameters. For the above problems, we provide the first hybrid quantum search algorithm based on the fixed-point and trail-and-error methods, where the matched multiphase Grover operations are trialed multiple times and the number of iterations increases exponentially along with the number of trials. The upper bound of expected queries as well as the optimal parameters are derived. Compared with Yoder’s algorithm, the query complexity of our algorithm indeed achieves the optimal scaling in λ for quantum search, which reconfirms the practicality of the fixed-point method. In addition, our algorithm also does not contain randomness, and compared with the existing deterministic algorithm, the query complexity can be reduced by about 1/3. Our work provides a new idea for the research on fixed-point and trial-and-error quantum search.展开更多
This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformatio...This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformation and multi-level matching strategies have been proven effective and successful as the experiments show while the control point database is established.展开更多
针对传统蚁群算法在移动机器人路径规划中存在搜索盲目性、收敛速度慢及路径转折点多等问题,提出了一种基于改进蚁群算法的移动机器人路径规划算法。首先,利用跳点搜索(Jump Point Search,JPS)算法不均匀分配初始信息素,降低蚁群前期盲...针对传统蚁群算法在移动机器人路径规划中存在搜索盲目性、收敛速度慢及路径转折点多等问题,提出了一种基于改进蚁群算法的移动机器人路径规划算法。首先,利用跳点搜索(Jump Point Search,JPS)算法不均匀分配初始信息素,降低蚁群前期盲目搜索的概率;然后,引入切比雪夫距离加权因子和转弯代价改进启发函数,提高算法的收敛速度、全局路径寻优能力和搜索路径的平滑程度;最后,提出一种新的信息素更新策略,引入自适应奖惩因子,自适应调整迭代前、后期的信息素奖惩因子,保证了算法全局最优收敛。实验仿真结果表明,在不同地图环境下,与现有文献结果对比,该算法可以有效地缩短路径搜索的迭代次数和最优路径长度,并提高路径的平滑程度。展开更多
光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该...光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该文提出了一种基于麻雀搜索算法优化的极限学习机(sparrow search algorithm-extreme learning machine,SSA-ELM)神经网络控制器的MPPT方法。与传统技术相比,该MPPT方法在稳定性、速度、超调和MPP的振荡等方面的效果均较好。使用MATLAB/Simulink平台进行仿真实验,验证了所提控制策略及理论分析的正确性。展开更多
针对跳点搜索(jump point search,JPS)算法在寻路过程中所存在的路径拐点多、中间搜索跳点数多、寻找跳点的过程中扩展节点数多和寻路时间较长等问题,提出改进双向动态JPS算法。改进算法动态定义正、反扩展方向上的目标点,动态定义启发...针对跳点搜索(jump point search,JPS)算法在寻路过程中所存在的路径拐点多、中间搜索跳点数多、寻找跳点的过程中扩展节点数多和寻路时间较长等问题,提出改进双向动态JPS算法。改进算法动态定义正、反扩展方向上的目标点,动态定义启发函数,并利用动态约束椭圆对算法的扩展区域加以限制,以区分椭圆内、外区域的扩展优先级。在算法从起点和目标点两个方向上分别向对方进行扩展的过程中,以寻找到的新的代价最小点为新椭圆的焦点,椭圆的方位和约束区域也随之动态调整。仿真结果表明,经过优化改进的双向动态JPS算法在一般地图中有一定的表现,在障碍物较少且目标点距离起点较近的室内环境地图中表现尤为良好。展开更多
为解决传统A^(*)寻路算法在搜索过程中会产生大量冗余节点,导致算法整体搜索效率低,运算内存消耗大等问题,从A^(*)算法的两个重要决策点出发,改进算法的代价评估函数与邻节点搜索策略,提出一种改进融合算法。首先,采用向量叉积与尺度平...为解决传统A^(*)寻路算法在搜索过程中会产生大量冗余节点,导致算法整体搜索效率低,运算内存消耗大等问题,从A^(*)算法的两个重要决策点出发,改进算法的代价评估函数与邻节点搜索策略,提出一种改进融合算法。首先,采用向量叉积与尺度平衡因子相结合的方法优化传统A^(*)算法的启发函数,减少A^(*)算法寻路过程中在最优路径周围产生的具有相同代价值的冗余节点,减少了对称路径的搜索;其次,融合跳点搜索(Jump point search, JPS)策略,通过逻辑判断实现路径的变步长跳跃搜索,避免了A^(*)算法逐层搜索效率低的弊端。在不同尺寸的栅格地图中进行仿真分析,发现改进融合算法相比于传统A^(*)算法,在路径长度基本相等的情况下,节点搜索数量约减少95%,且与传统JPS寻路算法相比,有效过滤了路径周围复杂形状障碍物产生的大量冗余跳点。最后,将改进融合算法应用于ROS移动机器人并进行对比实验以验证算法的可行性。实验结果表明:改进融合算法在获得高效安全的路径基础上,搜索效率相比于A^(*)算法可提高约94%。展开更多
为解决传统JPS(Jump Point Search)算法的拐点多和路径次优等问题,提出一种改进的跳点搜索算法。首先,根据地图可行率,对障碍物进行适应性膨胀,以保障安全距离;其次,结合方向性因素对启发函数进行调整,显著提高了路径搜索的目的性;最后...为解决传统JPS(Jump Point Search)算法的拐点多和路径次优等问题,提出一种改进的跳点搜索算法。首先,根据地图可行率,对障碍物进行适应性膨胀,以保障安全距离;其次,结合方向性因素对启发函数进行调整,显著提高了路径搜索的目的性;最后,提出了一种能剔除冗余节点的关键点提取策略,优化了初始规划后的路径,在保证路径最短的同时,显著减少了拓展节点和拐角。实验结果表明,与传统的JPS算法相比,所提算法能缩短路径长度并减少拐角数量,同时拓展节点数量平均减少19%,搜索速度平均提升21.8%。展开更多
基金supported by the National Science Council under Grant No. NSC98-2221-E-468-017 and NSC 100-2221-E-468-023the Research Project of Asia University under Grant No. 100-A-04
文摘In this study, we extend our previous adaptive steganographic algorithm to support point geometry. For the purpose of the vertex decimation process presented in the previous work, the neighboring information between points is necessary. Therefore, a nearest neighbors search scheme, considering the local complexity of the processing point, is used to determinate the neighbors for each point in a point geometry. With the constructed virtual connectivity, the secret message can be embedded successfully after the vertex decimation and data embedding processes. The experimental results show that the proposed algorithm can preserve the advantages of previous work, including higher estimation accuracy, high embedding capacity, acceptable model distortion, and robustness against similarity transformation attacks. Most importantly, this work is the first 3D steganographic algorithm for point geometry with adaptation.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11504430 and 61502526)the National Basic Research Program of China(Grant No.2013CB338002)
文摘For the unsorted database quantum search with the unknown fraction λ of target items, there are mainly two kinds of methods, i.e., fixed-point and trail-and-error.(i) In terms of the fixed-point method, Yoder et al. [Phys. Rev. Lett.113 210501(2014)] claimed that the quadratic speedup over classical algorithms has been achieved. However, in this paper, we point out that this is not the case, because the query complexity of Yoder’s algorithm is actually in O(1/λ01/2)rather than O(1/λ1/2), where λ0 is a known lower bound of λ.(ii) In terms of the trail-and-error method, currently the algorithm without randomness has to take more than 1 times queries or iterations than the algorithm with randomly selected parameters. For the above problems, we provide the first hybrid quantum search algorithm based on the fixed-point and trail-and-error methods, where the matched multiphase Grover operations are trialed multiple times and the number of iterations increases exponentially along with the number of trials. The upper bound of expected queries as well as the optimal parameters are derived. Compared with Yoder’s algorithm, the query complexity of our algorithm indeed achieves the optimal scaling in λ for quantum search, which reconfirms the practicality of the fixed-point method. In addition, our algorithm also does not contain randomness, and compared with the existing deterministic algorithm, the query complexity can be reduced by about 1/3. Our work provides a new idea for the research on fixed-point and trial-and-error quantum search.
基金Project supported by the National Oommission of Defense Science and Technotocjy(No.Y96-10)
文摘This paper discusses the approaches for automatical searching of control points in the NOAA AVHRR image on the basis of data rearrangement in the form of latitude and longitude grid. The vegetation index transformation and multi-level matching strategies have been proven effective and successful as the experiments show while the control point database is established.
文摘针对传统蚁群算法在移动机器人路径规划中存在搜索盲目性、收敛速度慢及路径转折点多等问题,提出了一种基于改进蚁群算法的移动机器人路径规划算法。首先,利用跳点搜索(Jump Point Search,JPS)算法不均匀分配初始信息素,降低蚁群前期盲目搜索的概率;然后,引入切比雪夫距离加权因子和转弯代价改进启发函数,提高算法的收敛速度、全局路径寻优能力和搜索路径的平滑程度;最后,提出一种新的信息素更新策略,引入自适应奖惩因子,自适应调整迭代前、后期的信息素奖惩因子,保证了算法全局最优收敛。实验仿真结果表明,在不同地图环境下,与现有文献结果对比,该算法可以有效地缩短路径搜索的迭代次数和最优路径长度,并提高路径的平滑程度。
文摘光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该文提出了一种基于麻雀搜索算法优化的极限学习机(sparrow search algorithm-extreme learning machine,SSA-ELM)神经网络控制器的MPPT方法。与传统技术相比,该MPPT方法在稳定性、速度、超调和MPP的振荡等方面的效果均较好。使用MATLAB/Simulink平台进行仿真实验,验证了所提控制策略及理论分析的正确性。
文摘针对跳点搜索(jump point search,JPS)算法在寻路过程中所存在的路径拐点多、中间搜索跳点数多、寻找跳点的过程中扩展节点数多和寻路时间较长等问题,提出改进双向动态JPS算法。改进算法动态定义正、反扩展方向上的目标点,动态定义启发函数,并利用动态约束椭圆对算法的扩展区域加以限制,以区分椭圆内、外区域的扩展优先级。在算法从起点和目标点两个方向上分别向对方进行扩展的过程中,以寻找到的新的代价最小点为新椭圆的焦点,椭圆的方位和约束区域也随之动态调整。仿真结果表明,经过优化改进的双向动态JPS算法在一般地图中有一定的表现,在障碍物较少且目标点距离起点较近的室内环境地图中表现尤为良好。
文摘为解决传统A^(*)寻路算法在搜索过程中会产生大量冗余节点,导致算法整体搜索效率低,运算内存消耗大等问题,从A^(*)算法的两个重要决策点出发,改进算法的代价评估函数与邻节点搜索策略,提出一种改进融合算法。首先,采用向量叉积与尺度平衡因子相结合的方法优化传统A^(*)算法的启发函数,减少A^(*)算法寻路过程中在最优路径周围产生的具有相同代价值的冗余节点,减少了对称路径的搜索;其次,融合跳点搜索(Jump point search, JPS)策略,通过逻辑判断实现路径的变步长跳跃搜索,避免了A^(*)算法逐层搜索效率低的弊端。在不同尺寸的栅格地图中进行仿真分析,发现改进融合算法相比于传统A^(*)算法,在路径长度基本相等的情况下,节点搜索数量约减少95%,且与传统JPS寻路算法相比,有效过滤了路径周围复杂形状障碍物产生的大量冗余跳点。最后,将改进融合算法应用于ROS移动机器人并进行对比实验以验证算法的可行性。实验结果表明:改进融合算法在获得高效安全的路径基础上,搜索效率相比于A^(*)算法可提高约94%。
文摘为解决传统JPS(Jump Point Search)算法的拐点多和路径次优等问题,提出一种改进的跳点搜索算法。首先,根据地图可行率,对障碍物进行适应性膨胀,以保障安全距离;其次,结合方向性因素对启发函数进行调整,显著提高了路径搜索的目的性;最后,提出了一种能剔除冗余节点的关键点提取策略,优化了初始规划后的路径,在保证路径最短的同时,显著减少了拓展节点和拐角。实验结果表明,与传统的JPS算法相比,所提算法能缩短路径长度并减少拐角数量,同时拓展节点数量平均减少19%,搜索速度平均提升21.8%。
