面向低强度无线网络信号接收谱参数估计研究

针对以北斗卫星导航信号为代表的亚纳秒级的低强度无线网络信号在定位中难以获取精确时间估计及角度估计,且易受环境噪声影响,使其定位精度不高等难题,本文提出了基于亚纳秒级的低强度无线网络信号接收谱参数估计方法。首先通过抽样方式,将发射信号抽样为多维独立子信号并独立建模,通过构造噪声空间与子信号空间在对应列向量正交化的基础上精确获取TOA估计;随后利用复数域映射,在获取TOA估计基础上采取比对方式精确地获取DOA估计。最后对本文参数估计方法进行了精度分析。测试数据显示：与 PM算法、ESPRIT算法相比,本文技术在TOA及DOA估计上更为精确;同时在信号强度低且背景噪声干扰严重的情况下,本文方法仍可有效的维持参数估计精度。     

铽－甲基吲哚乙酰丙酮三元配合物发光过程研究

测定和分析了ＲＥ．Ｌ１．Ｌ２（ＲＥ＝Ｔｂ（Ⅲ）、Ｇｄ（Ⅲ），Ｌ１＝３Ｍ（３甲基吲哚－１－乙酰基丙酮），Ｌ２＝ＴＰＰＯ、Ｐｈｅｎ、Ｄｉｐｙ）三元配合物的荧光光谱、磷光光谱、磷光寿命及变温荧光光谱等．讨论了Ｔｂ（Ⅲ）与配体之间的能级匹配和Ｌ１与Ｌ２的三重态之间传能的问题，说明了影响这些三元配合物荧光效率的主要因素及其发光过程．     

FTIR－PAS技术在卟啉类化合物中的应用（Ⅳ）──稀土乙酰丙酮－meso－四－（α－萘基）四苯并卟啉配合物的红外光谱

研究了ｍｅｓｏ－四－（α－萘基）四苯并卟啉及其Ｄｙ，Ｈｏ，Ｅｒ，ＴＭ，Ｙｂ，Ｌｕ乙酸丙酮形成的配合物在３６００～２２０ｃｍ－１范围内的傅里叶变换红外光声光谱（ＦＴＩＲ－ＰＡＳ），对主要谱带进行了经验归属。结果表明，四－（ａ－萘基）四苯并卟啉与稀土乙酰丙酮配合物中稀土金属离子配位削弱了乙酰丙酮环上Ｍ—Ｏ键的伸缩振动，使此谱带向低波数位移。金属敏感港带出现在～１５１３，～１３２３～１０９０，１０５３和～２５０ｃｍ－１。     

Mössbauer studies of mixed-valence spin-crossover iron complexes with a hexadentate tripod ligand

The spin-crossover behaviors of mixed-valence iron compounds [Fe^IIH₃L][Fe^IIIL](NO₃)₂ (1) and [Fe^IIH₃L^Me][Fe^IIIL^Me](NO₃)₂ (2) have been investigated by ⁵⁷Fe Mössbauer spectroscopy, where H₃L is a hexadentate N₆ tripod ligand containing three imidazole groups and H₃L^Me is its 2-methylimidazole derivative. Deconvolution analyses of the Mössbauer spectra revealed that a two-step SCO (LS Fe^II–LS Fe^III→HS Fe^II–LS Fe^III→HS Fe^II–HS Fe^III) proceeds in each compound on elevating the temperature. Compound 2 exhibited lower spin-transition temperatures than 1. “Frozen-in effect” was observed below 120 and 50 K for 1 and 2, respectively.     

Vibrational dynamics of the organometallic compound triarylorganoantimony (V) SbPh<Subscript>3</Subscript>[O<Subscript>2</Subscript>CC(OH)Ph<Subscript>2</Subscript>]<Subscript>2</Subscript>

A complete normal coordinate analysis was performed for five-coordinate non-rigid triarylantimony diester SbPh₃(O₂CR)₂, known to be a bioactive molecule, using Wilson G-F matrix method and Urey Bradley force field. The study of vibrational dynamics was performed using the concept of group frequencies and band intensities.      

对Reissner-Nordstrm-anti-de Sitter黑洞Hawking隧穿辐射的研究

在考虑粒子间的自引力相互作用后,首先采用Parikh-Wilczek的半经典隧穿方法对带电粒子与不带电粒子在Reissner-Nordstrm-anti-de Sitter黑洞视界处的隧穿辐射特征进行了研究.其次,推广复路径方法对该黑洞的辐射谱进行研究.两种方法所得的结果都支持Parikh-Wilczek的观点,即黑洞的隧穿率Bekenstein-Hawking熵变有关,真实的辐射谱不是纯热谱.     

增长速度对合作网络参与者节点度分布的影响

采用率方程对合作网络自组织演化模型进行解析,得到参与者节点度分布服从Yule-Simon分布,这种分布可以用漂移幂律分布近似.分析参与者节点增长速度与参与者节点度分布之间的关系,发现随节点增长速度加快,参与者节点度分布远离幂律,表明节点增长速度是除优先连接之外的另一个影响合作网络拓扑性质的重要因素.通过对城市公交网络和科研合作网络的实证研究,验证了度分布解析结果的正确性.结合实证研究,探讨了合作网络中参与者节点增长速度的形成机制及其实际意义.     

10－5000 伏下电子被多原子分子CF4, CF3H, C2F4, C2F6, 及 C2H3F3散射总结面的计算

利用可加性规则和光学势方法计算了能量在10-5000 eV范围内电子被多原子分子CF4, CF3H, C2F4, C2F6, 及 C2H3F3的总结面，并与已有的实验结果和理论计算进行了比较，与这些结果符合得很好。对于CF4, CF3H, C2F4, C2F6, 及 C2H3F3在1000eV以上没有实验数据，本文对实验研究提供了对比和预测的数据。     

Attractive target wave patterns in complex networks consisting of excitable nodes

This review describes the investigations of oscillatory complex networks consisting of excitable nodes,focusing on the target wave patterns or say the target wave attractors.A method of dominant phase advanced driving(DPAD) is introduced to reveal the dynamic structures in the networks supporting oscillations,such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks.The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns.Therefore,the center(say node A) and its driver(say node B) of a target wave can be used as a label,(A,B),of the given target pattern.The label can give a clue to conveniently retrieve,suppress,and control the target waves.Statistical investigations,both theoretically from the label analysis and numerically from direct simulations of network dynamics,show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large,and all these attractors can be labeled and easily controlled based on the information given by the labels.The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.