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   matrix features 的翻译结果: 查询用时:0.175秒
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matrix features
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  矩阵特征
     The SAR image is classified by using the feature vector which is composed of wavelet texture energy features, the gray-level co-occurrence matrix features and the tone of filtered SAR image with tree wavelet.
     该方法采用由树型小波中频纹理能量特征、灰度共生矩阵特征、树型小波滤波后的灰度组成的特征矢量对SAR图像进行分类。
短句来源
  矩阵性质
     Through the development of the multidelaytime 4th order accumulation slice structure of Gas noise sine signal and Hankel matrix features composed of these accumulation, the highresolution sine signal evaluation method is proposed from the accumulation of delay time.
     在含噪正弦信号频率估计方法中,通过开发高斯色噪声中正弦信号的四阶累积量切片结构、以及由这些累积量构成的Hankel矩阵性质,提出了多滞后时刻累积量的高分辨正弦信号频率估计方法。
短句来源
  矩阵结构特征
     If an (N×P) matrix W is the geological data matrix, where N is the number of samples and P the number of variables, then the matrix features an N much greater then P. Previously, an (N×N) matrix, which is usually a high dimension matrix, must be formed in Q-mode factor analysis.
     设(N×P)矩阵W是地质数据矩阵(N是样品数,P是变量数),这一矩阵结构特征是N大大于P. 以前Q式因子分析必须形成一个通常是高维的N×N矩阵.
短句来源
  “matrix features”译为未确定词的双语例句
     In the aspect of imagery processing, the author propose a method of using GLCM(Gray-Level Co-occurrence Matrix) to calculate the texture characteristic of SAR images. And the SAR image is classified by using the feature vector that is composed of the Gray Level Co-occurrence matrix features and gray of pixels.
     在图像处理方面,本文使用了利用灰度共生矩阵(Gray-Level Co-occurrence Matrix)计算SAR海冰图像纹理特征的统计方法,然后结合SAR图像像素灰度值组成特征矩阵,并以此作为智能识别系统进行分类的依据。
短句来源
     Simulations show that this method can efficiently segment multi-texture images into several regions according to their different texture properties, and the segmentation error ratio is lower than the method of combining co-occurrence matrix features extraction with K-means clustering.
     仿真结果证明,该方法能有效地分割出区域特性不同的纹理,且错分率低于共生矩阵和K均值聚类相结合的分割方法。
短句来源
     Low temperature plasma technique with fluorocarbon compounds atmosphere is the latest development for surface modification of various materials. Through introducing fluoro group to the surface of the matrix by plasma treatment, the matrix features low surface energy and many special properties.
     介绍了以氟碳化合物为气氛的低温等离子体技术进行各种材料的表面改性的最新进展 ,指出等离子体技术可在各种材料表面引入含氟基团 ,以获得低能表面 ,从而使材料获得各种特殊的性能。
短句来源
     150 sidescan sonar images for mud,sand and rock seafloors are classified using the presented three-dimensional feature vector,and recognition rates of maximum 96.7% and minimum 90.7% are achieved. These same 150 seafloor images are also classified using the conventional gray level co-occurence matrix features,and a recognition rate of 87.3% is achieved,which shows that the presented seafloor classification method has better classification performance.
     利用该特征矢量(QUM,TEM,σ)对泥、沙、石三种类型海底的150幅侧扫声纳图像进行分类实验,获得了最高96.7%、最低90.7%的识别率,而利用常用的灰阶共生矩阵方法的分类识别率为87.3%,表明本文方法能较好地用于海底底质分类.
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      matrix features
    Forx>amp;gt;0.25 up to 0.7 the structural matrix features are almost similar to those of crystalline TlAsSe2.
          


    If an (N×P) matrix W is the geological data matrix, where N is the number of samples and P the number of variables, then the matrix features an N much greater then P. Previously, an (N×N) matrix, which is usually a high dimension matrix, must be formed in Q-mode factor analysis. Therefore it has only a restricted application owing to the high dimension matrix. The R-Q mode factor analysis, however, only needs to form a ( P × P ) matrix W'W(usually P<50). On the basis of W'W, we...

    If an (N×P) matrix W is the geological data matrix, where N is the number of samples and P the number of variables, then the matrix features an N much greater then P. Previously, an (N×N) matrix, which is usually a high dimension matrix, must be formed in Q-mode factor analysis. Therefore it has only a restricted application owing to the high dimension matrix. The R-Q mode factor analysis, however, only needs to form a ( P × P ) matrix W'W(usually P<50). On the basis of W'W, we can extract both R-mode and Q-mode factors simultaneously by invoking the Eckart - young theorem, which makes the actual application of Q-mode factor possible. Another advantage of the R-Q mode factor analysis is that Q-mode factor and R- mode factor can be shown simultaneously on a plan. Then we can observe the relationship between the variables, between the samples, between the variables and factors and between the samples and variables on the plan.

    设(N×P)矩阵W是地质数据矩阵(N是样品数,P是变量数),这一矩阵结构特征是N大大于P.以前Q式因子分析必须形成一个通常是高维的N×N矩阵.由于这一高维矩阵,Q式因于分析的应用受到限制.然而R-Q式因子分析只需形成一个(P×P)矩阵W'W(通常P<50).根据W'W,我们用Eckart-young理论同时提取R式和Q式因子,这使得Q式因子分析的实际应用成为可能.R一Q式因子分析的另一优点是R式因子解和Q式因子解可以同时表示在一张平面图上,然后我们就可以在这张图上考察变量之间、样品之间,变量和因子之间以及变量和样品之间的关系.

    By employing the elastic and elastic plastic finite element method(FEM), the effects of matrix feature on the stress transfer mechanisms of short fiber composites are studied. In the calculation, the variations in matrix modulus, yield strength and hardening modulus are considered. It is concluded that large deformation of matrix is harmful to the improvement of the mechanical performances of the composites.

    er of Short Fiber CompositesTX@康国政@高庆@刘世楷IntroductionIncomposites,loadsareappliedtothematrixandtransferedtothefibersthroughthefib...

    This paper suggests a texture classification algorithm based on the feature symbol random field (FSRF). FSRF is a 2 D representation of the image's bank information. In FSRF, symbol value of a pixel gives out its structure function in texture region and is more valuable than the gray value for texture classification. Meanwhile, several co occurrence matrix features are driven from the FSRF which are more powerful than energy features. This paper also suggests a Hierarchical scheme which leads to...

    This paper suggests a texture classification algorithm based on the feature symbol random field (FSRF). FSRF is a 2 D representation of the image's bank information. In FSRF, symbol value of a pixel gives out its structure function in texture region and is more valuable than the gray value for texture classification. Meanwhile, several co occurrence matrix features are driven from the FSRF which are more powerful than energy features. This paper also suggests a Hierarchical scheme which leads to 96% correct ratio in the included experiments, while the gray value based method 67.5% and bank energies based method 75%.

    提出了一种基于特征符号随机场描述的纹理分类方法。特征符号随机场是纹理图象的一种二维描述,它采用离散的符号来描述纹理图象的结构性特征。文中的纹理分类实验表明:以特征符号随机场为基础的统计模型,更充分地描述了纹理图象的本质特征,在单频段多方向滤波条件下能够取得理想的分类结果。

     
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