认知Ad hoc网络中基于凸优化的功率控制算法

针对认知Ad hoc网络的特点,构建了相应的网络模型,提出了一种基于凸优化理论的分布式功率控制算法。在分析系统内部干扰的基础上,以最大化网络效用值为目标,以认知用户的发射功率为求解对象,建立了一个通用的数学优化模型。在凸优化理论的指导下,通过引入辅助变量和变量的对数变换,将该模型转变为等价的凸优化模型,采用拉格朗日对偶法对该模型进行求解,得到了分布式的功率迭代算法。仿真实验表明：与其他算法相比,该算法在满足系统约束条件的前提下,取得更好的系统性能。     

介质阻隔放电合成臭氧的研究

研究了介质阻隔放电中臭氧生成随放电时间、场强及氧气压力变化的关系，从电子能量的角度得到了在接近常压条件下臭氧生成的最优化条件，最佳约化场强度（３３０Ｔｄ），并测定了本系统中臭氧的热解常数。     

非正弦功率探讨和非线性阻抗下瞬时正弦分解法

对传统电工理论中关于非正弦功率的定义及计算方法进行了探讨和分析，指出其不足，介绍了非正弦电流、功率的瞬时分析法，对正弦电压在非线性阻抗情况下的非正弦电流提出了瞬时正弦分解法，并借助于ａｂｃ－αβ坐标变换对三相对称系统中的瞬时有功、无功 电流和肯时有功、无功功率进行分析计算，同时将该分析方法在非正弦电压下的分解作了推广。     

Riesz Decomposition Theorems for Continuous-time Fuzzy Supermartingales

Compared with discrete-time fuzzy supermartingales, the structure and the properties of trajectories for continuous-time fuzzy supermartingales are more complex. This paper focuses on Riesz decomposition for continuous-time fuzzy supermartingales. The concepts of two types of Riesz decomposition (Riesz decomposition and level Riesz decomposition) are given and some necessary and sufficient conditions of that a continuous-time fuzzy supermartingale has Riesz decomposition are discussed in detail.     

羧酸亚硝酰酯热分解反应的量子化学研究

用ＵＨＦ／ＡＭ１方法研究羧酸亚硝酰热分解反应的机理，研究结果表明，消除ＮＯ形成ＲＣ（Ｏ）Ｏ是该反应所循的途径。     

Realization of Orthogonal Wavelets Adapted to Fabric Texture for Defect Detection

The wavelet adapted to the fabric texture can be developed from the orthogonal and normal series which are selected randomly by means of Monte Carlo method and optimized by adding certain constraint conditions. Then the fabric image can be decomposed into the subimages by the adaptive wavelet transform and the horizontal and vertical texture information will be perfectly contained in the subimages. Therefore this method can be effectively used for the automatic inspection of the fabric defects.     

Acquisition of nutrients from organic resources by mycorrhizal autotrophic plants

Summary Evidence exists to suggest that mycorrhizal fungi are capable of producing enzymes allowing them to access carbon, nitrogen and phosphorus from complex organic resources in soil. This facility is mainly demonstrated in ectomycorrhizal and ericaceous endomycorrhizal fungi associated with highly organic soils and climatically stressed environments. These data support a direct nutrient cycling hypothesis proposed for tropical ectomycorrhizal forests. In terms of forest succession, the evidence agrees with a major contribution of the mycorrhizal symbiosis in late stages of the succession, where elemental cycling becomes increasingly more conservative and process rates limited by biotic factors. Here, tree growth benefits from direct nutrient cycling mediated by their mycorrhizal symbionts.     

空域色噪声背景下双基地MIMO雷达角度估计

空域有色噪声会导致现有多输入多输出(multiple input multiple output,MIMO)雷达算法性能下降,甚至完全失效.针对空域色噪声背景下双基地MIMO雷达联合波离角(direction of departure,DOD)和波达角(direction of arrival,DOA)估计问题,分析了...     

Short-run wavelet-based covariance regimes for applied portfolio management

Decisions on ass et allocations are often determined by covariance estimates from historical market data. In this paper, we introduce a wavelet-based portfolio algorithm, distinguishing between newly embedded news and long-run information that has already been fully absorbed by the market. Exploiting the wavelet decomposition into short- and long-run covariance regimes, we introduce an approach to focus on particular covariance components. Using generated data, we demonstrate that short-run covariance regimes comprise the relevant information for periodical portfolio management. In an empirical application to US stocks and other international markets for weekly, monthly, quarterly, and yearly holding periods (and rebalancing), we present evidence that the application of wavelet-based covariance estimates from short-run information outperforms portfolio allocations that are based on covariance estimates from historical data.