In order to enhance the classification information of the single training sample, each train-ing sample is combined with its reconstructed image gotten by perturbing a few significant singular values into a new version of the original sample. 为了从单训练样本中获取更多的信息,训练样本与其受扰动的少数较大的奇异值的重构图组合成新样本。
It is important that signals be reconstructed by making use of amplitude spectrum and partial time-domain sample. 利用幅度谐与部分时域采样值来重构信号是极为重要的。
These applications require that the reconstructed CAD model can accurately restore the sample of object for different degrees. 这些应用都不同程度地要求重构的CAD模型能准确的还原实物样件。