稀疏性 的英文怎麼說

中文拼音 [xīshūxìng]
稀疏性 英文
openness
  • 稀 : Ⅰ形容詞1 （事物出現得少） rare; scarce; uncommon 2 （事物之間距離遠; 空隙大） sparse; scattered 3...
  • 疏 : Ⅰ動詞1 （疏通） dredge （a river etc ）2 （疏忽） neglect 3 （分散; 使從密變稀） disperse; scatte...
  • 性 : Ⅰ名詞1 （性格） nature; character; disposition 2 （性能; 性質） property; quality 3 （性別） sex ...
  • 稀疏 : few and scattered; few and far between; thin; sparse
  1. Chronically sick pigs often suffer from a partial alopecia characterized by a thinning of the bristles.

    慢性病豬通常有局部脫毛，特點是鬃毛變稀疏。
  2. The anatomical and ultrastructural research in the cotyledon of antirrhinum majus indicated : cutin membrane and sparse epidermal trichome occurred on the surface of cotyledon. stomata protruded appreciably over the epidermis, the ratio of palisade mesophyll and spongy mesophyll was low, the previous evidence showed structural charecater of shade leaf

    通過對金魚草子葉的組織學和細胞學研究，發現其表皮角質膜薄，具稀疏表皮毛，氣孔略突出於表皮，柵欄組織與海綿組織比例小，故具有陰性葉的結構特徵。
  3. This paper adopts an adaptive learning algorithm based on hierarchy clustering to update user profile, which continuously abstract the cancroids of one class of optimum information from the feedback flow of system, which effectively shield the learning process from plenty of feedback noises produced by distorted threshold and sparseness of initial information, which also can imitate artificial feedback approximately to perfect the intelligence of adaptive learning mechanism

    摘要本文採用一種基於層次聚類的自適應學習策略，從系統反饋的信息流中，動態提取一類最優信息的質心更新用戶模型，有效屏蔽了閾值失真和初始信息稀疏造成的大量反饋噪聲，並且能夠近似模仿人工反饋，完善自適應學習機制的智能性。
  4. Due to the hard core repulsion, the distribution function of electrons was compressed effectively. thus, we hope the new model has different properties from the standard bariev model with open boundary

    由於存在硬芯勢，電子在鏈上的分佈變得稀疏，開邊界的有芯模型具有不同於標準bariev模型的性質。
  5. Based on the clustering property of the basis function of sparse coding, a basis function initialization method using fuzzy c mean algorithm is proposed to help the energy function of sparse coding to converge to a better local minimum for recognition. experimental results show that the classification and the sparseness of the features are both improved

    經過模糊c均值聚類初始化后的基函數能夠讓稀疏編碼的能量函數收斂到一個更有利於識別的局部最小點，試驗結果表明特徵的分類性和稀疏性都得到了提高。
  6. Tricepstrum equalization algorithm ( btea ) and super - exponential ( se ) algorithm based on block data estimation is studied, and these algorithms use hos explicitly. their performance, such as estimation variance and bias, is analyzed. a kind of sparse cross cumulant and sparse equalizer is proposed to simplify the se algorithm, and the simulating results show efficient reduction in complication

    ?研究了幾種直接使用高階統計量的演算法，包括基於數據段估計的倒三譜演算法和超指數演算法，分析了演算法的估計方差和偏差等性能；由於超指數演算法計算量較大，不利於實時均衡，利用水聲通道的稀疏性，提出了一種基於稀疏互四階累積量和稀疏權的演算法，有效降低了超指數演算法的計算量。
  7. The connection matrix of a network is usually large and sparse. in this article, the auther brought forward a method to reduce the connection matrix order, which was help for saving operation time and space when it is stored in computer

    通過引進矩陣運算元並藉助于矩陣的分塊運算，針對網路聯絡矩陣的稀疏性，提出一種含表決系統的網路聯絡矩陣的降階方法，節約了演算法的運行時間和存儲空間。
  8. This paper applies generalized multipler method to translate convex quadratic programs with equal constraints and non - negative constraints into simple convex quadratic programs with non - negative constraints. the new algorithm is gotten by solving the simple quadratic program. it avoids the computation of inverse matrix and exploits sparsity structure in the matrix of the quadratic form. the results of numerical experiments show the effectiveness of the algorithm on large scale problems

    根據廣義乘子法的思想，將具有等式約束和非負約束的凸二次規劃問題轉化為只有非負約束的簡單凸二次規劃，通過解簡單凸二次規劃來得到解等式約束和非負約束的凸二次規劃新演算法，新演算法不用求逆矩陣，這樣可充分保持矩陣的稀疏性，用來解大規模稀疏問題.數值結果表明：在微機486 / 33上就能解較大規模的凸二次規劃
  9. Second, a new wavelet - based denoising method without free parameters is proposed which is based on the sparseness and decorrelation properties of the discrete wavelet transform

    首先提出了一種基於相關鄰域模型的sar圖像rcs重構方法。其次，利用離散小波變換的稀疏性和減相關性進行sar圖像濾波。
  10. It can find that the data is high dimension and sparse. we bring forward hsmbk and hssca algorithms to code with the problem

    針對實驗數據的高維性、稀疏性等特徵，我們提出了hsmbk和hssca兩個聚類演算法。
  11. But with the system scale enlarging, its efficiency gradually declines and some problems such as sparsity, scalability and early rater will appear

    但隨著系統規模的擴大，它的效能會逐漸降低，暴露出矩陣稀疏性、擴展性和早期級別等問題。
  12. To conclude a sparse solution, we present an improved algorithm for least squares support vector machines, and prove its effect by an experiment

    對原有的最小二乘支持向量機在稀疏性上進行了改進，並通過實驗，對改進后的最小二乘支持向量機的分類效果進行了驗證。
  13. A model - based recommendation algorithm was proposed, which uses multi - level association rules ( mar ) to alleviate those problems about data sparseness and scalability of the recent recommendation algorithm

    摘要提出一種基於多層關聯規則（ mar ）的推薦演算法，著重解決目前推薦演算法的稀疏性問題和可擴展性問題。
  14. Abstract a model - based recommendation algorithm was proposed, which uses multi - level association rules ( mar ) to alleviate those problems about data sparseness and scalability of the recent recommendation algorithm

    摘要提出一種基於多層關聯規則（ mar ）的推薦演算法，著重解決目前推薦演算法的稀疏性問題和可擴展性問題。
  15. Sad is able to differentiate models in form of subroutines, fully exploit the sparsity of the models and need few additional operations. it is concluded that sad is very suitable for the process models that have relatively simple computational structure and consist mainly of polynomials

    符號自動微分具有可對子程序形式的函數求導、可以充分利用模型的稀疏性、無需輔助操作的優點，非常適合針對結構相對簡單、計算式以多項式為主的過程系統模型求導。
  16. In the first and second section of chapter 1 we introduce the model of dimension reduction problem, put forward the concepts of dimension - reduction function and embedding function, and make a classification for the dimension reduction problem ; in section 1. 3 we discuss " the curse of dimension " and the sparsity of high - dimensional space ; in section 1. 4 we discuss " intrinsic dimension " and its estimation based on the model of dimension reduction

    第一章首先提出了降維的模型和定義，討論了相關的問題；第三節討論「維數禍根」現象和高維空間的稀疏性，通過實例分析其對高維空間的數據分佈特性具體影響；第四節討論了本徵維數及其估計的基本問題。
  17. In this paper, we consider the optimal parameter vector a of the modified incomplete gauss _ seidel method ( migs ). we prove that the spectral radius function of the iterative matrix t of migs with parameter vector is strictly monotonic decreasing with respect to a satisfying 0 e if the classical gauss _ seidel method converges for a z _ matrix. some properties of the left and right eigenvectors corresponding to the largest eigenvalue in modulus are given, too. these results are useful to find an optimal parameter for migs

    目前主要的方法有兩類：一是充分利用所給矩陣a的特點，採用適當的主元素選取策略，使分解出的因子盡可能地保持稀疏性；二是迭代法。對于第二種方法，迭代矩陣的選取具有決定作用。只有選取的迭代矩陣的譜半徑小於1才能保證迭代法收斂。
  18. Instead, there needs to store only the original coefficient matrix, some auxiliary matrices for the preconditioner and several vectors in the iteration methods. further, the core of the iteration is the matrix - vector multiplication and the solution of the auxiliary equations corresponding to the preconditioner. if the solution of the auxiliaries spend not very much, the computational cost in each iteration step will be very cheap, due to the fact that the sparsity of the matrix can be exploited sufficiently

    與直接法相比，迭代法只需存儲原系數矩陣、對應于預處理的幾個輔助矩陣與少量幾個向量，且迭代中除求解輔助線性方程組外，其餘的計算主要是稀疏矩陣與向量乘積，從而能充分利用稀疏性減少計算量，但迭代法的收斂速度一般與系數矩陣的譜分佈有關。
  19. There are several problems in traditional systems from the current b2c website electronic commerce personalization recommendation system : data sparsity, the commodities which are purchased or rated by users only occupy the total commodity number about 1 % ; new project problem, the new user and the new commodity which doesn ’ t be purchased or rated can ’ t be recommended ; solely recommend means, long data processing and low recommendation precision

    本文通過對當前b2c網站的電子商務個性化推薦系統分析，發現傳統的推薦系統有如下問題:數據稀疏性問題，用戶購買或評分的只佔總商品數的1 %左右;新項目問題，對于未被購買或評分的新商品、新用戶一般不能進行推薦;推薦方法單一、數據處理耗時過長以及推薦精度不高的問題。
  20. This situation makes the quality of recommendation systems decreases dramatically. to address this issue, we proposed a collaborative filtering recommendation algoritm based on item rating prediction. this method predicted ratings of un - rated item by the similarity of items, and then the nearest neighbors of target user were calculated with a new similarity measure method

    針對用戶評分數據的極端稀疏性，本文提出了基於項評分預測的irprec協同過濾推薦演算法，通過計算項之間的相似性，初步預測用戶對未評分項的評分，然後採用一種新穎的相似性度量方法計算用戶的最近鄰居。
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