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  参数反演
    This paper focus on the parameter inversion and the measurement method of optical constant of Diamond-like Carbon (DLC)——a new film material.
    本文主要研究薄膜新材料——类金刚石(Diamond-Like Carbon,简写为DLC)薄膜光学特性的测量和参数反演
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  参数反演
    This paper focus on the parameter inversion and the measurement method of optical constant of Diamond-like Carbon (DLC)——a new film material.
    本文主要研究薄膜新材料——类金刚石(Diamond-Like Carbon,简写为DLC)薄膜光学特性的测量和参数反演
短句来源
  参数反演
    This paper focus on the parameter inversion and the measurement method of optical constant of Diamond-like Carbon (DLC)——a new film material.
    本文主要研究薄膜新材料——类金刚石(Diamond-Like Carbon,简写为DLC)薄膜光学特性的测量和参数反演
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  parameter inversion
Test of Source-Parameter Inversion of Intensity Data
      
The multi-parameter inversion of elastic wave equation in a half-space within the Born approximation is studied.
      
The specific procedure is to conduct a 2D interface-constrained CEMP inversion using 2D seismic and log data followed by a property parameter inversion of the anomalous bodies using gravity and seismic data by the stripping technique.
      
Then, using multi-parameter inversion and integrated multi-attribute analysis, we predict the favorable reservoir distribution quantitatively and setni-quantitatively to clarify the distribution of high-yield zones.
      
We have proposed an AVA and physical parameter inversion algorithm.
      
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Surface parameters inversion by using Polarimetric SAR includes the inversion of the soil surface permeability , correlation length and RMS height. The retrieval of scattering parameters can be viewed as a mapping problem from the domain of measured signals to the range of surface/medium characteristics that quantify the observed medium. To date, parameter inversion has been based largely on empirical models. Empirical models have usually avoided the nonuniqueness problem by limiting the validity of the...

Surface parameters inversion by using Polarimetric SAR includes the inversion of the soil surface permeability , correlation length and RMS height. The retrieval of scattering parameters can be viewed as a mapping problem from the domain of measured signals to the range of surface/medium characteristics that quantify the observed medium. To date, parameter inversion has been based largely on empirical models. Empirical models have usually avoided the nonuniqueness problem by limiting the validity of the model to a single parameter and a narrow range. This limit on the range of validity requires that multiple empirical models be created-one model for each parameter. In this study, the Spaceborn Imaging Radar SIR-C data at L and C band was used to perform the inversion of bare surface parameters. A BP neural network based on IEM model was developed to carry out the inversion, and a test method was also developed. The combination of a scattering model (IEM) and NN makes it possible to perform inversion with higher accuracy and in real time. Backscat-tering coefficients computed from the model inverted surface parameters was proved to be good, compared with the real backscattering coefficients from radar image.

人工神经网络(Artificial Neural Network)是一个由独立处理单元以一定拓扑结构高度连接而成的并行分布式信息处理结构,适于解决各种非线性问题。积分方程(Integrated Equation Model)单散射模型可模拟各种地表参数条件下裸露地表后向散射系数。以IEM为基础生成训练数据,用L波段和C波段SIR-C HH,VV极化单散射后向散射系数数据为神经网络输入,通过后向反馈(BP)神经网络模型可同时反演得到裸露地表条件下地表介电常数、地表相关长度和均方根高度等地表参数。

Although the Normalized Difference Vegetation Index(NDVI) time-series data derived from NOAA/AVHRR,SPOT/VEGETATION and MODIS,has been successfully used in research regarding global vegetation change,land cover classification and biophysical parameters inversion.However,due to effect of cloud and atmospheric conditions,residual noise in the NDVI time-series data will induce erroneous results in our further quantitive analysis.In this paper,some general reconstructing methods are introduced,including Maximum...

Although the Normalized Difference Vegetation Index(NDVI) time-series data derived from NOAA/AVHRR,SPOT/VEGETATION and MODIS,has been successfully used in research regarding global vegetation change,land cover classification and biophysical parameters inversion.However,due to effect of cloud and atmospheric conditions,residual noise in the NDVI time-series data will induce erroneous results in our further quantitive analysis.In this paper,some general reconstructing methods are introduced,including Maximum Value Compositing(MVC),the Best Index Slope Extraction(BISE),Media Iteration Filter(MIF),Temporal Window Operation(TWO),Fourier Transform(FT) and Savitzky-Golay Filter(S-G Filter).With the development of change detection research,it is necessary to reconstruct the NDVI time-series data sets in order to provide high-quality data for the study of vegetation response to global climate change.

基于NOAA/AVHRR、SPOT/VEGETAT ION以及MOD IS等卫星影像得到的归一化植被指数(NDV I,N orm alized D ifference V egetation Index)时序资料已经在植被动态变化监测、宏观植被覆盖分类和植物生物物理参数反演方面得到了广泛的应用,但由于受云层、天气等因素的影响,NDV I数据集存在大量的噪声,因此对NDV I时间序列数据集进行重建,提高NDV I数据集质量的研究逐步受到关注。对近年来普遍使用的几种NDV I时间序列数据集重建方法(最大值合成、最佳指数斜率提取、中值迭代滤波、时间窗内的线性内插、傅里叶变换、S-G滤波)进行了详细介绍并评述了这些方法的优缺点。

 
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