改进的支持向量机低分辨雷达目标分类算法

针对雷达目标识别系统中存在库外目标、各特征属性分类性能不一致,低分辨雷达不同类别目标特征值分布区间混叠的问题。文中基于支持向量机分类算法,对目标样本特征值进行置信度分析,获得置信区间,利用代价函数确定拒识门限,对库外目标以及混叠区域目标进行拒识分析;并根据训练样本先验识别率使用注水原理分配特征属性权重;在此基础上利用支持向量机进行目标识别。雷达实测数据实验结果表明,引入置信拒识分析与注水分配加权后,分类器性能得到了有效改善。     

Test for Heteroscedasticity in Partially Linear Regression Models

Testing heteroscedasticity determines whether the regression model can predict the dependent variable consistently across all values of the explanatory variables. Since the proposed tests could not detect heteroscedasticity in all cases, more precisely in heavy-tailed distributions, the authors established new comprehensive test statistic based on Levene's test. The authors built the asymptotic normality of the test statistic under the null hypothesis of homoscedasticity based on the recent theory of analysis of variance for the infinite factors level. The proposed test uses the residuals from a regression model fit of the mean function with Levene's test to assess homogeneity of variance. Simulation studies show that our test yields better than other methods in almost all cases even if the variance is a nonlinear function. Finally, the proposed method is implemented through a real data-set.     

非线性光机械系统中的弱力探测

从理论上研究了包含光学参量放大器的非线性腔光机械系统的弱力探测性能.一方面,发现通过调节光学参量放大器的非线性增益以及输入光场与腔场之间的有效失谐,可以减小压缩正交中约14 dB的量子噪声,从而将弱力探测灵敏度提高2倍以上.另一方面,分析了非线性腔结合零差测量产生的反作用噪声相消现象并且实现量子非破坏测量的方法.     

Erratum to: Hesperomyces virescens (Fungi,Ascomycota, Laboulbeniales) attacking Harmonia axyridis (Coleoptera,Coccinellidae) in its native range

正Published online:14 March 2014óScience China Press and Springer-Verlag Berlin Heidelberg 2014Erratum to:Chin.Sci.Bull.(2014)59(5–6):528–532DOI 10.1007/s11434-013-0060-1In the original publication of this paper,the first name and the last name of the first author has been documented     

TRIZ理论在风电产品设计中的应用

介绍了TRIZ理论的产生及其理论体系,重点介绍了其在产品设计创新中应用最为广泛的TRIZ矛盾理论,包括矛盾的定义、分类及相关的解决原理,并结合实例说明了TRIZ理论的矛盾理论在风电产品设计中的应用及在企业中推广TRIZ理论的重要意义。     

The effects of the non-breaking surface wave-induced vertical mixing on the forecast of tropical cyclone tracks

The Weather Research and Forecasting model(WRF)is configured for the region of(15°–41°N,105°–135°E),which covers the same area with the MASNUM(Key Lab.Marine ScienceNumerical Modeling,State Oceanic Administration)wave-tide-circulation coupled operational forecast system.Three numerical experiments are implemented to investigate the effects of the real-time forecasted sea surface temperature(SST)and the nonbreaking wave-induced vertical mixing(Bv)on the track forecast of all 33 tropical cyclones(TC)in the model domain area during 2008 and 2011.The first experiment employs NCEP FNL(NCEP final analysis)SST as WRF’s bottom condition as the Control run,which is also the default setup of WRF.The second and third experiments use real-time forecasted SST from the MASNUM forecast system with and without Bv,respectively.The forecasted track results are compared with Japan Meteorological Agency’s best track data.For 24-h forecast,the averaged TC position error of Experiment with Bv is reduced by 9%compared to the Control experiment,while the forecasted track error of Experiment without Bv is reduced by only2%compared to the Control experiment.For the 48-h forecast,the averaged track errors are reduced by 10%and6%with Bv and without Bv compared to the Control experiment,respectively.These results suggest that the real-time forecasted SST can improve the performance of WRF in forecasting TC track,and the Bv plays an important role in reducing the forecast error of TC track.Comparatively,Bv can improve more on the track of stronger TC.