The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple structure.However,these devices are uns...The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple structure.However,these devices are unsuitable for cross-point architectures because of the difficulty in controlling the random filament formation that results in large fluctuations in the threshold voltage during operation.In this study,we investigated the unidirectional threshold transition characteristics associated with an Ag/GST/HfO_(x)/Pt-based bilayer selector and demonstrated the occurrence of a low leakage current(<1×10^(-11) A) and low distribution of the threshold voltage(Δ0.11 V).The bilayer structure could control the filament formation in the intermediate state through the insertion of an HfO_(x) tunneling barrier.By stacking a bilayer selector with NiO_(x)based resistive random-access memory,the leakage and programming currents of the device could be significantly decreased.For the crossbar array configuration,we performed equivalent circuit analysis of a one-selector oneresistor(1S1R) devices and estimated the optimal array size to demonstrate the applicability of the proposed structure.The maximum acceptable crossbar array size of the 1S1R device with the Ag/GST/HfO_(x)/Pt/Ti/NiO_(x)/Pt structure was 5.29×10^(14)(N^(2),N=2.3×10^(7)).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
基金financially supported by the National Research Foundation of Korea (NRF)(No.2016R1A3B1908249)。
文摘The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple structure.However,these devices are unsuitable for cross-point architectures because of the difficulty in controlling the random filament formation that results in large fluctuations in the threshold voltage during operation.In this study,we investigated the unidirectional threshold transition characteristics associated with an Ag/GST/HfO_(x)/Pt-based bilayer selector and demonstrated the occurrence of a low leakage current(<1×10^(-11) A) and low distribution of the threshold voltage(Δ0.11 V).The bilayer structure could control the filament formation in the intermediate state through the insertion of an HfO_(x) tunneling barrier.By stacking a bilayer selector with NiO_(x)based resistive random-access memory,the leakage and programming currents of the device could be significantly decreased.For the crossbar array configuration,we performed equivalent circuit analysis of a one-selector oneresistor(1S1R) devices and estimated the optimal array size to demonstrate the applicability of the proposed structure.The maximum acceptable crossbar array size of the 1S1R device with the Ag/GST/HfO_(x)/Pt/Ti/NiO_(x)/Pt structure was 5.29×10^(14)(N^(2),N=2.3×10^(7)).
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%。
