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Search Results: 1 - 10 of 71750 matches for " 颛孙少帅 "
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基于W态的量子确定性密钥分发方案
少帅,陈红
量子电子学报 , 2014,
Abstract: 提出了一种基于W态的量子确定性密钥分发方案,方案采用在量子信道中传输更加稳定的W态作为承载信息的粒子,利用量子相干特性以及一串公开的信息序列S作为密钥分发的关键,在兼顾传输粒子稳定性的前提下能够达到54.54%的密钥分发效率,与使用GHZ态相比,在效率相差无几的情况下保证粒子在传输过程中具有更强的鲁棒性。安全分析表明,此方案能经受窃听者采取的截获——转发(重发)攻击和纠缠攻击两种攻击方式,确保通信安全可靠。同时,该方案在执行过程中不涉及任何幺正操作,简单便捷。
基于GHZ态纠缠交换的量子确定性密钥分发方案
少帅,陈红,蔡晓霞
量子电子学报 , 2015,
Abstract: 为了提高确定性密钥分发效率,提出了基于GHZ态纠缠交换的量子确定性密钥分发(QuantumDeterministicKeyDistribution,QDKD)方案,方案充分利用量子力学纠缠交换的原理,通信双方通过共享一对GHZ粒子态,在纠缠、测量操作后接收者Bob可根据发送者Alice发送的经典信息推断出确定密钥,该协议与其他基于GHZ纠缠态的QDKD方案不同之处在于,使用的两个GHZ粒子态制备操作且粒子分发操作由Bob完成,安全分析表明窃听者的窃听行为会被及时发现。所提出的方案是高效的,除去用于窃听检测的粒子,所剩的粒子全部用于信息传输,能够达到60%的密钥分发效率,且方案可操作性强。
基于强化学习的无线自组网络多节点干扰策略
少帅,杨俊安,刘辉,黄科举
- , 2018, DOI: 10.13195/j.kzyjc.2017.0365
Abstract: 为了实现无线自组网络通信拒止的干扰需求,构建无线自组网络模型,并针对该模型提出一种基于强化学习理论的未知拓扑网络多节点干扰策略选择算法,以实时交互的方式进行在线学习.该算法无需获悉网络拓扑等先验知识,仅以网络流数目作为反馈信息,以多节点联合干扰的方式逐步学习最佳干扰节点.在不同参数的无线自组网中的仿真结果表明,所提算法在累积阻断网络流方面优于现有算法,且在新的奖赏标准下,所提算法仍具有优异的干扰性能.
采用双层强化学习的干扰决策算法
An Algorithm for Jamming Decision Using Dual Reinforcement Learning

少帅,杨俊安,刘辉,黄科举
- , 2018, DOI: 10.7652/xjtuxb201802010
Abstract: 为解决强化学习算法在干扰决策过程中收敛速度慢的问题,提出了一种采用双层强化学习的干扰决策算法(DRLJD)。首先对等效通信参数进行建模,模型减少了待学习参数的个数,降低了搜索空间的维度;然后利用降维后的搜索空间指导干扰参数选择,避免随机选择导致干扰性能差的缺点;最后利用选择的干扰参数施加干扰,并根据环境反馈进一步降低搜索空间的维度,通过不断交互的方式加快算法的收敛速度。此外,将以往的干扰经验以先验信息的形式加入到系统的学习进程中,进一步缩短了系统的学习时间。针对构造的干扰问题实验表明,DRLJD算法经过200次交互便学习到优异的干扰策略,小于现有算法所需600次交互,且先验信息的利用进一步降低了对交互次数的要求。以提出的新的奖赏标准作为奖赏依据,算法能够在未知通信协议情况下以牺牲交互时间为代价学习到最佳干扰策略。
A novel algorithm for jamming decision using dual reinforcement learning (DRLJD) is proposed to accelerate convergence rate of reinforcement learning algorithms in jamming decision. First, a model of equivalent communication parameter is constructed to reduce both the number of unlearned parameters and the dimension of the search space. Secondly, the search space with reduced dimension is used to choose jamming parameters and to avoid worse jamming performance caused by random selection. Finally, the selected parameters are used to take jamming action, and to reduce the dimension of search space from the environment feedback information. The convergence rate of the algorithm is accelerated by constant interaction. Moreover, previous jamming experiences are used as prior information to further shorten the learning time of the system and to accelerate the convergence rate. The proposed DRLJD algorithm is validated by taking experiments on some jamming problems. Simulation results show that the algorithm obtains the optimal or suboptimal jamming strategy with 200 interaction times which is less than 600 interaction times of existing algorithms, and the use of prior information further reduces the requirements for the number of interactions. When the new reward standard is used as a basis for reward the proposed algorithm could learn the optimal jamming strategy at the expense of interaction times in the case that communication protocols are not known
未知拓扑无线自组网络多节点干扰决策算法
An Algorithm of Multi??Nodes Jamming Decision in Blind Wireless Ad??hoc Networks

少帅,杨俊安,刘辉,黄科举
- , 2018, DOI: 10.7652/xjtuxb201806014
Abstract: 为满足战场环境下无线自组网络通信拒止的干扰需求,提出了一种未知拓扑无线自组网络多节点干扰决策算法(CUCB)。首先,根据战场无线自组网络结构特点构建泊松点过程(PPP)网络模型,并利用其模拟网络中数据流传输过程;其次,随机对PPP网络中多个节点进行干扰,通过监听确认帧信息或侦察节点活跃度判断阻断网络流数,根据干扰结果构造节点相关性矩阵;最后,利用强化学习与环境实时交互的特点,在干扰过程中不断更新节点相关性矩阵并将其用于后续节点选择。所提算法无需获悉目标网络拓扑结构、节点重要性等先验信息,仅以阻断网络流数目或节点活跃性作为奖赏标准,适用网络类型更为广泛。仿真结果表明,对不同参数下的无线自组网络进行干扰,所提算法在鲁棒性方面优于现有算法,在累积阻断网络流数量方面比联合利用探索算法提高了27.1%。
An algorithm focus on multi??nodes jamming decision is proposed to fulfill the need of interdicting information transmission in wireless Ad??hoc networks. Firstly, a model of Poisson point process (PPP) network is constructed in terms of the structure of wireless Ad??hoc networks, and then it is used to simulate the process of data transmission. Secondly, random interference to multiple nodes are performed, and the number of stopped network flows is counted by monitoring ACK information or reconnoitering nodes activities. A correlation matrix is constructed from jamming effects. Finally, the correlation matrix is continuously updated in jamming process by taking the advantage of interaction in time of reinforcement learning and is used for the selection of subsequent nodes. The proposed algorithm does not need to have a priori knowledge of information such as network topology or importance of nodes, and interaction is only needed in learning nodes correlation matrix which would be helpful when choose nodes to jam. Simulation results by jamming wireless Ad??hoc in different circumstances and a comparison with the joint slotted exploit explore learning show that the proposed interdiction algorithm increases by 27??1% in accumulate stopped flows, and its robustness is superior to existing algorithms
论药名演变的不可逆性及当前的对策
王旭,复猷
中国中药杂志 , 1990,
Abstract: <正>自五十年代始,呼吁药名书写要规范化的若干篇专文曾在多家医药报刊上陆续刊出,然而事实上,不规范的药名却始终是随处可见。例如,1988年4月举行的淮海经济区17地市首届中医学术交流会的论文中,不规范的药名多达100个以上。而学术界最有影响的《中医杂志》,1989年第1期内也出现了川朴、苡米、石决、
必须十分珍视矿物药资源
王旭,复猷
中国中药杂志 , 1990,
Abstract: <正>我国的矿物药起源甚早。现存最早的医学著作《五十二病方》中记载了雄黄、丹砂、硝石、礜石等20种矿物药的临床应用,武威出土的汉代医简及医圣张仲景的书中也分别用到十多种矿物药,汉代大经学家郑玄甚至把矿物药“石胆、丹砂、雄黄、礜石、磁石烧之三日三夜,其烟上着,鸡羽扫取以注疮”写进了《周礼》注。时至当代,高等医药院校教材《方剂学》(1975年版)所收的197首正方中,就有40
基于数据重传的电压岛NoC能量优化
宗亮,李克秋
大连理工大学学报 , 2014, DOI: 10.7511/dllgxb201402013
Abstract: 在支持电压岛的片上网络体系结构中,考虑供应电压对数据重传的影响,提出了一种新的能耗模型,并提出了基于电压岛划分、IP核映射和路由算法设计的架构方法.该方法针对电压岛划分、IP核映射和路由算法设计等问题,不仅考虑了IP核的计算能耗,还考虑了IP核之间数据在重传下的数据通信能耗问题.实验结果表明,在考虑数据重传的情况下,该设计方法能有效地降低系统能耗.
山苍子核油钠皂十二烷基苯磺酸钠复合润滑冲洗液的性能及应用效果
黄振国,,仇志
地质与勘探 , 1983,
Abstract: 山苍子核油钠皂润滑冲洗液是润滑性能良好的金刚石钻探润滑减阻剂.去年华东地勘局二六一、二六二和二六九大队进行了较大规模的生产试验,用山苍子核油钠皂润滑冲洗液共钻进了4735米钻孔,取得了初步的效果.同时也发现这种润滑冲洗液若皂化不够充分,会在钻杆和钻头
灰色系统理论在煤层气含量预测中的应用
田敏,赵永军,鹏程
煤田地质与勘探 , 2008,
Abstract: 煤层含气量是一个受多因素影响的反映煤层含气性的定量指标。以晋城矿区为例,根据煤层气地质基本理论,利用改进的斜率关联度法,分析了煤层气含量的影响因素;进而,由灰色多变量静态模型GM(0,N)预测了煤层气含量,并与多元回归分析的结果进行比较。结果表明,用改进斜率关联度进行灰色关联分析所确定的煤层气含量的主要影响因素是可信的;由GM(0,N)模型预测煤层含气量所需样本数据少,原理简单,计算方便,且预测精度较高。
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