基于高光谱曲线的马铃薯与其他主要作物光谱差异性分析

[目的]文章以马铃薯关键生长期——结薯期为测量时点,以马铃薯和玉米、大豆、水稻为研究对象,开展高光谱曲线特征差异性研究。[方法]为更好地描述马铃薯与其他作物的光谱差异,创建高光谱反射率差异性指数、高光谱一阶导数差异性指数、高光谱红边幅值差异性指数、高光谱曲率差异性指数及高光谱植被指数差异性指数。[结果](1)马铃薯与玉米、大豆、水稻3种作物光谱曲线具有明显差异,马铃薯与玉米的反射率值在480nm附近蓝色波段位置差异最显著,差异性指数值为67.866%,与大豆、水稻的最大差异性指数值分别为49.068%、57.559%,均位于550nm附近绿色波峰位置;(2)作物光谱曲线经一阶导数变换运算,马铃薯与其他作物间的光谱差异被显著放大,在近红外波段放大程度最显著;(3)马铃薯与玉米、大豆、水稻高光谱曲率差异性指数最大值均位于波长750nm附近,差异性指数值分别为78.365%、63.471%、80.882%;(4)常用植被指数中,比值植被指数、增强型植被指数可显著区分马铃薯与玉米、大豆、水稻。[结论]差异性分析结果为农作物空间分布遥感识别提供了技术支撑。     

The informative sample size for dynamic multiple equation systems with moving average errors

Abstract  The problem considered here, is that of finding suitable conditions for dynamic economic systems that exclude the existence of observationally equivalent structures. Here observational equivalence refers to equality of distributions or first and second moments of a small finite sample from the observable process. It is shown, that under these conditions we may act as if the lagged endogenous variables are nonrandom exogenous variables, when global identifiability is investigated.     

谱减法语音增强

本文就语音信号及各噪声信号的特点进行了分析研究,提出了一种具有高稳定性且适用范围广的语音信号增强算法,并更进一步提出一种采用谱减法的语音增强方法。     

分析微生物检测技术在食品检验中的应用

本文针对微生物检测技术检测指标、技术特征、必要性等内容展开分析,结合免疫学技术、光谱技术、代谢学技术、分子生物学技术、质谱检测技术、传感器技术在食品检验中的应用要点,目的在于提升食品检验结果可靠性,为技术体系的不断完善奠定基础。     

高分辨率铁尾矿遥感光谱特征分析与信息提取

遥感监测尾矿是矿山调查和监管的科学方法,也是地理国情监测的基础内容。研究了铁尾矿遥感影像解译标志和光谱特征,建立铁尾矿遥感信息的提取技术流程。利用尾矿光谱特征与纹理结构的特点,构建了铁尾矿遥感增强处理的RTI数学模型。并以唐山地区的铁尾矿及固体废弃物作为研究区,分析了模型的影响因子和有效性。为尾矿资源的自动监测和目标提取提供了新的处理手段。     

优化参数对CPM-PSWF信号性能的影响

基于椭圆球面波信号的连续相位调制（Continuous Phase Modulation Based on Prolate Spheroidal Wave Function,CPM-PSWF）方法是一种新颖的数字调制方式,调制参数的优化与其调制信号性能有着直接联系。分析不同调制参数对CPM-PSWF信号性能的影响,优化选择调制参数,对获得能量聚集性和功率效率都较高的CPM信号具有重要意义。首先,对基于椭圆球面波信号的CPM信号进行描述;其次,采用韦尔奇(Welch)谱密度估计法,对时间带宽积、调制指数、关联长度等不同参数对CPM-PSWF调制信号的功率谱密度和带宽特性的影响进行了仿真分析。实验结果表明,选用0阶椭圆球面波信号,小时间带宽积、调制指数和符号进制数越小,关联长度越大时,CPM-PSWF信号具有频谱带外高频滚降快、占用带宽小的特点。     

Nonparametric Inference of Value-at-Risk for Dependent Financial Returns

The article considers nonparametric estimation of value-at-risk(VaR) and associated standard error estimation for dependentfinancial returns. Theoretical properties of the kernel VaRestimator are investigated in the context of dependence. Thepresence of dependence affects the variance of the VaR estimatesand has to be taken into consideration in order to obtain adequateassessment of their variation. An estimation procedure of thestandard errors is proposed based on kernel estimation of thespectral density of a derived series. The performance of theVaR estimators and the proposed standard error estimation procedureare evaluated by theoretical investigation, simulation of commonlyused models for financial returns, and empirical studies onreal financial return series.     

遥感影像土地覆盖(LC)专题信息提取方法研究

在对研究区背景本底知识和遥感数据光谱知识充分分析的基础上,挖掘谱间结构,得出各典型地物的光谱空间特征及相互分离规则。结合原有GIS数据,用地学知识和DTM模型纠正初步分类图,得到较理想的分类结果。尝试提出各专题信息分层提取,分类结果加权叠加的方法。     

Do shocks have permanent or transitory effects on tourist inflow? An application of stationarity test with structural breaks: evidence reexamined for Gilgit-Baltistan,Pakistan

ABSTRACT

Do shocks affect tourist inflows permanently or temporarily? To examine this question, we consider a region in Northern Pakistan, Gilgit-Baltistan, known for its natural and scenic beauty and with a history of huge tourist inflows, both domestic and international. The tourist arrivals from significant source markets are investigated using univariate and Lagrange Multiplier (LM) unit root tests with two structural breaks to examine if shocks to the time path of visitors’ inflow are permanent or transitory. According to the results, the univariate and LM unit root test with two breaks reject the unit root null for all major source markets. The findings suggest transistory effects rather than permanent effects of shocks on the growth path of tourist arrivals to Gilgit-Baltistan. This result further predicts the sustainability of the tourism sector in the region in the long run.     

A proof of asymptotic normality for some VARX models

Here we present a proof of the asymptotic normality of least squares estimates for stable multivariate autoregressive models excited by a deterministic second order input signal.