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最优子空间
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  optimal subspace
     Recognition of radar target based on optimal subspace using range profile
     雷达目标一维距离像识别中的最优子空间
短句来源
     We given the exact estimation of dn+(mk、σσ; L1 ) and the optimal subspace of d2n-1+ ( mk、σ、1 , 0, L1).
     并给出其单边宽度d_n~+(m_(k,σ,1);L,)的精确估计值,以及达到其d(2n-1)~+((?) _(k,σ,1)) L,)的最优子空间
短句来源
     In this paper the factor analysis method is presented to transform orthogonally the optimal subspace, which is obtained from partial least squares regression.
     本文提出采用因素分析方法 ,对偏最小二乘回归的最优子空间进行正交变换 .
短句来源
     The optimal subspace is used to extract feature of target for improving classification performance.
     利用最优子空间能够提取到更优的特征 ,改善目标识别性能。
短句来源
  “最优子空间”译为未确定词的双语例句
     The exact estimate of mean dimension for the class of tempend splines of order r is determined, and it is also proved that the subspace of tempered splines is asymptotic optimal for average width of the sobolev dass W~r_2(R) in metric L_q, 2≤q≤.
     确定了r阶缓增样条类的平均维数的精确估计,并证明了缓增样条函数类是Soborev类Wr2(R)在L2(R)尺度下的一个最优子空间
短句来源
     Experimental results demonstrate that our method can find the optimal ASM shape model rapidly and improve the performance of ASM significantly.
     实验结果表明,本文提出的方法能够快速、准确地找到最优子空间,从而极大地提高主动表面模型的性能。
短句来源
     In this paper,We obtain the exact values of n-width Wr∞ in space Lq (1≤q≤∞, in the sense of Kolmogorov),when restrictions are placed on the approximation.
     本文考虑了r阶光滑类W_s~r,在Lq空间中带限制的逼近空间的Kolmogorov n-宽度问题。 给出了1≤q<∞,S=∞时的精确估计及相应的最优子空间
短句来源
     A case study demonstrates that the original variable set is divided into several variable groups after the orthogonal transform, each of which is corresponding to a new factor in the subspace such that its explanatory ability is improved.
     案例研究表明 ,经过正交变换后 ,原始变量被分为若干变量组 ,每个变量组分别对应于最优子空间中的一个因素 ,从而提高了对最优子空间的内涵分析能力
短句来源
     Genetic algorithm is combined with the eigen subspace to build an optimal eigen subspace for the recognition.
     该方法首先对原数据样本进行特征提取变换,再采用遗传算法选取最优特征矢量,由此组成最优子空间
短句来源
  相似匹配句对
     Radar target recognition based on optimal eigen subspace
     基于最优特征矢量子空间的雷达目标识别
短句来源
     Complemented Subspaces
     余子空间
短句来源
     and m which is a linear subspace of Fn,may not be convex.
     F~n的线性子空间(?)
短句来源
     Combined Subspace Based Optimal Feature Extraction and Face Recognition
     基于组合子空间最优特征抽取及人脸识别
短句来源
     Optimal Control of Trajectory
     最优轨线控制
短句来源
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  optimal subspace
The exact values of these widths are calculated and an optimal subspace with the optimal linear operator (for the δ-linear width) are identified.
      
For the Kolmogorovn-width we show that forn≥r there exists an optimal subspace of splines of degreer-1 withn-r fixed simple knots depending onp.
      
Instead of pursuing a single optimal subspace, we develop an ensemble learning framework based on random sampling on all three key components of a classification system: the feature space, training samples, and subspace parameters.
      
In other words, such dimension reduction approaches can only generate one single optimal subspace to represent the original data space.
      
Since the optimal subspace to which f is projected depends on f, the approximation is called adaptive.
      
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Extremal problem on uniform approximation for class of 2π-periodic func- tions W~rH~w is solved by class of 2π-periodic functions W_∞~(r+k), where w is a ncave modulus of continuity and r=0, 1, 2, …, k≥1 is an integer. From this, coit is shown that if F_N is an optimal subspace for Kolmogorov width d_N (W_∞~(r+k),C), the it is optimal for d_N(W~rH~w, C) and F_N~r=:F_r_r is asymptotic optimal subspace for class of non-periodic functions W~rH~w[0, 2π]in metric C, where _r=Span{1, x,…, x~r}. These theorems generalize...

Extremal problem on uniform approximation for class of 2π-periodic func- tions W~rH~w is solved by class of 2π-periodic functions W_∞~(r+k), where w is a ncave modulus of continuity and r=0, 1, 2, …, k≥1 is an integer. From this, coit is shown that if F_N is an optimal subspace for Kolmogorov width d_N (W_∞~(r+k),C), the it is optimal for d_N(W~rH~w, C) and F_N~r=:F_r_r is asymptotic optimal subspace for class of non-periodic functions W~rH~w[0, 2π]in metric C, where _r=Span{1, x,…, x~r}. These theorems generalize the results of Kor- meieuk and Lorentz.

本文解决了2π周期函数类W~rH~w由2π周期函数类W_∞~(r+k)最佳一致逼近这一极值问题,这里w为上凸连续模,r=0,1,…,k≥1为整数;并由此证得一切Kolmo-gorov宽度d_N(W_∞~(r+k),C)的N维最优子空间F_N均是N维K宽度d_N(W~rH~wC)的最优子空间,推广了的结果。同时,本文还证得F_N~=:F_N_r为非周期函数类W~rH~w[0,2π]在C空间内的强渐近的最优子空间;其中_r=Span{1,x,…,x~r};深化了Lorentz的结果.

In this paper,We obtain the exact values of n-width Wr∞ in space Lq (1≤q≤∞, in the sense of Kolmogorov),when restrictions are placed on the approximation.

本文考虑了r阶光滑类W_s~r,在Lq空间中带限制的逼近空间的Kolmogorov n-宽度问题。给出了1≤q<∞,S=∞时的精确估计及相应的最优子空间

In this paper, we studied the Class mk、σ、p ={ f∈ Lpk+σ}| Qk,σ(D)f || P≤1,∫02π Qk、σ(D)f(x)dx = 0} of smooth functions, which defined by the linear differentialoperator Qk、σ(D) = Dσmultiply from j=1 to k(D- tj). We given the exact estimation of dn+(mk、σσ; L1 ) and the optimal subspace of d2n-1+ ( mk、σ、1 , 0, L1). The paper improved.[3]

本文研究由实系数线性微分算子Q_(k,σ)(D)=Dσsum form j=1 to (?)(D-tj)所定义的2π周期函数类,integyal form n=0 to 2π(Q_(k,σ))(D)f(X)dx=O;并给出其单边宽度d_n~+(m_(k,σ,1);L,)的精确估计值,以及达到其d(2n-1)~+((?)_(k,σ,1)) L,)的最优子空间。本文的结果推广了。

 
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