eigenspace 中文意思是什麼

eigenspace 解釋
本照間
  1. This is a two - objective optimization problem. to solve the problem, two methods are presented, which are the weighted method and the eigenspace method

    文中還給出了兩種確定權值的方法，即加權法和特徵空間法，並通過計算機模擬對這兩種方法進行了比較。
  2. In term of the relative gaps of the eigenvalues and the singular values, the additive relative perturbation bounds of eigenspace and singular subspace of matrices are investigated and some new results are obtained

    摘要根據特徵值和奇異值的相對分離情況，研究了矩陣特徵空間和奇異空間的加法相對擾動界，得到一些新的擾動界。
  3. In the fourth chapter we deal with the eigenspace ( see 4. 1 ) and singular space ( see 4. 2 ) perturbations

    第四章討論了特徵空間（見4 1 ）和奇異空間（見4 2 ]的擾動。
  4. Additive relative perturbation bounds for eigenspace and singular subspace

    矩陣特徵空間和奇異空間相對擾動界
  5. Firstly this paper introduced the principle of fisher linear discriminant function, and then present the subspace lda algorithm which project the data that is in high dimension space to eigenspace that is in low space and then maximize discriminant coefficient

    本文介紹了fisher線性判別準則原理和實現過程，然後引入subspacelda方法，用pca將高維圖像數據投影到低維的特徵臉空間，再用lda最大化判別系數。
  6. In training process, we use kernel - based fisher discrimination analysis ( kfda ) method to train the input sample vectors. the method has been used in face recognition and has been demonstrated better recognition capability than other methods ( pca, kpca, svm ). we calculate the optimal subspace wopt and project the sample gait sequences to wopt, then get the tracks of the sequences, calculate the track centroid and calculate the exemplar projection centroid of the sequences in the same class, and the exemplar projection centroid represents the class template. to test the class of a gait sequence, we also project the test sequence to the eigenspace, and calculate the track centroid, then calculate the euclidean distance of the test sequence tracking centroid with the sample sequences ’ exemplar projection centroids. and the class which the test sequence belongs to is the one that the sample sequence which the euclidean distance is shortest belongs to

    該方法在人臉識別的研究中已有採用並在同樣測試條件下取得比其他識別方法更好的識別性能。採用kfda方法取得最優特徵空間wopt ，把步態樣本序列映射到wopt中，取得樣本序列在特徵空間中的軌跡，計算軌跡質心，把同類樣本序列的軌跡質心進行平均求得該類的標本投影軌跡質心，作為該類的模板。在識別時，將測試序列也投影到特徵空間中，取得序列軌跡質心，對測試序列軌跡質心與樣本的標本投影軌跡質心計算它們的歐氏距離。
  7. Coherent interference suppression with eigenspace - based beamformer

    基於特徵空間的相干干擾抑制技術
  8. A modified eigenspace - based algorithm for adaptive beamforming

    一種改進的基於特徵空間自適應波束形成演算法
  9. Research on an ameliorated spatial smoothing technology based on eigenspace

    一種改進的特徵子空間平滑技術研究
  10. Then, eigenspace transformation based on pca is applied to time - varying project

    然後，應用主成分分析（ pca ）進行特徵提取和壓縮。
  11. We emphasized the selection of the eigenvector which used to create the eigenspace

    針對其在組成特徵投影空間時特徵向量選擇問題的做了重點研究。
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