在基于分段线性模型的正交频分复用(orthogonal frequency division multiplexing,OFDM)时变信道估计中,存在模型参数估计精度受到载波间干扰(inter-carrier interference,ICI)影响的问题。为此,本文采用ICI自消除技术,抑制了导频子载波...在基于分段线性模型的正交频分复用(orthogonal frequency division multiplexing,OFDM)时变信道估计中,存在模型参数估计精度受到载波间干扰(inter-carrier interference,ICI)影响的问题。为此,本文采用ICI自消除技术,抑制了导频子载波的ICI,改善了模型参数的估计性能。此外,还推导了单抽头Jakes信道条件下模型参数估计均方误差的表达式,理论分析表明,与基本的分段线性模型方法相比,本文方法可以使均方误差下降约13dB。仿真结果验证了在多抽头信道和大的多普勒扩展条件下,本文方法也能明显提高ICI抑制能力,从而得到更好的系统误码性能。展开更多
This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging...This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.展开更多
部分线性度量误差模型(Partial linear measurement error model)是经典的部分线性模型的推广．在此模型中,我们假定解释变量含有度量误差．本文,我们把经验似然推广到部分线性度量误差模型,得到了非参数的Wilk's定理．我们的方法...部分线性度量误差模型(Partial linear measurement error model)是经典的部分线性模型的推广．在此模型中,我们假定解释变量含有度量误差．本文,我们把经验似然推广到部分线性度量误差模型,得到了非参数的Wilk's定理．我们的方法可以用来构建置信区间(域),也可以用来检验．数值模拟表明,我们的方法在构建的置信区间长度以及覆盖率方面有很好的结果．展开更多
文摘在基于分段线性模型的正交频分复用(orthogonal frequency division multiplexing,OFDM)时变信道估计中,存在模型参数估计精度受到载波间干扰(inter-carrier interference,ICI)影响的问题。为此,本文采用ICI自消除技术,抑制了导频子载波的ICI,改善了模型参数的估计性能。此外,还推导了单抽头Jakes信道条件下模型参数估计均方误差的表达式,理论分析表明,与基本的分段线性模型方法相比,本文方法可以使均方误差下降约13dB。仿真结果验证了在多抽头信道和大的多普勒扩展条件下,本文方法也能明显提高ICI抑制能力,从而得到更好的系统误码性能。
基金Supported by Shanghai Universities First-class Disciplines Project,Discipline name:Fisheries(A),the National Natural Science Foundation of China(No.NSFC41276156)the National High Technology Research and Development Program of China(863 Program)(No.2012AA092303)+1 种基金the Shanghai Science and Technology Innovation Program(No.12231203900)CHEN Yong’s involvement was supported by the Shanghai Ocean University
文摘This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.
基金supported by the National Natural Science Foundation of China(Grant No.11571025Key Grant No.11331011)+2 种基金the BCMIISthe Beijing Natural Science Foundation(Grant Nos.1142003L140003)
文摘部分线性度量误差模型(Partial linear measurement error model)是经典的部分线性模型的推广．在此模型中,我们假定解释变量含有度量误差．本文,我们把经验似然推广到部分线性度量误差模型,得到了非参数的Wilk's定理．我们的方法可以用来构建置信区间(域),也可以用来检验．数值模拟表明,我们的方法在构建的置信区间长度以及覆盖率方面有很好的结果．
