稀疏矩陣計算 的英文怎麼說

中文拼音 [xīshūjǔzhènjìsuàn]
稀疏矩陣計算 英文
sparse matrix computation
  • 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...
  • 矩 : 名詞1. （畫直角或正方形、矩形用的曲尺） carpenter's square; square2. （法度; 規則） rules; regulations 3. [物理學] moment
  • 陣 : Ⅰ名詞1 （作戰隊伍的行列或組合方式） battle array [formation]: 布陣 deploy the troops in battle fo...
  • 計 : Ⅰ動詞1 （計算） count; compute; calculate; number 2 （設想; 打算） plan; plot Ⅱ名詞1 （測量或計算...
  • 算 : Ⅰ動詞1 （計算數目） calculate; reckon; compute; figure 2 （計算進去） include; count 3 （謀劃;計...
  • 稀疏 : few and scattered; few and far between; thin; sparse
  • 矩陣 : [數學] matrix; array
  • 計算 : 1 （求得未知數） count; compute; calculate; reckon; enumerate 2 （考慮; 籌劃） consideration; pla...
  1. ( 4 ) on the efficient method for the dynamical core of the new generation multi - scale forecasting model i ) we present a new multi - level sparse approximate inverse preconditnioner for the complicated 3 - d helmholtz equations in the new generation weather forecasting model. as a result, the new sparse approximate inverse preconditioned gcr and gmres algorithms are given and successfully applied in the dynamical core. numerical tests show that the new algorithms perform very efficiently, and can greatly improve the efficiency of numerical model

    對此，本文提出了一種基於逐層門限技術的近似逆矩陣稀疏模式預選方法，並構造了相應的稀疏近似逆預條件子，結合gcr演算法和g州[ r衛s演算法，首次將逐層門限稀疏近似逆預條件子應用於新一代多尺度預報模式動力內核的實際計算，數值實驗表明這里給出的方法可以大大提高數值模式的計算效率。
  2. Second, this paper studied the core technologies for developing the cae system for construction curtain wall, such as sparse matrix storage and processor for fea, parametric design and engineering modeling and so on

    然後針對建築幕墻結構計算機輔助工程系統所涉及的與有限元分析相關的稀疏矩陣存儲及求解技術、系統參數化設計技術以及工程建模技術等關鍵技術進行了較深入的研究。
  3. This problem arises from the circuit layout of vlsi designs, interconnection networks, sparse matrix computations, error - correcting code designs, data structures, biology, etc, which has extensive backgrounds

    圖的嵌入問題是從稀疏矩陣的計算、數據結構、 vlsi電子線路設計和分子生物學等問題中提取出來的數學模型，有著廣泛的應用背景。
  4. Numerical results show the dynamic deflation for the implicitly restarted block lanczos method is effective for computing the multiple or clustered eigenvalues of a large sparse symmetric matrix

    數值結果表明，動態收縮的隱式重新開始塊lanczos方法，對計算大型稀疏對稱矩陣的重特徵值或密集特徵值是有效的。
  5. The kanerva ' s sparse distributed memory ( sdm ) tackles the problem of training large data patterns and extendes the storage mode of existing computer. but it ' s address array produced randomly ca n ' t reveal the distribution of patterns and it has ' t the ability of function approximation for its learning rule

    Kanerva的稀疏分佈存儲（ sdm ）模型解決了大維數樣本的訓練問題，推廣了現有計算機的存儲方式。但其地址矩陣的隨機預置方式不能反映樣本的分佈，並且sdm的學習方式使之不能用於函數逼近及時間序列預測問題。
  6. The fft of helmholtz equation on the regular domain is studied. and the multifrontal algorithm is used to solve the matrix equations in computational electromagnetics. finally, the finite - difference approximate forms of maxwell equations and the despres transmission condition are discussed

    為了充分提高演算法的計算效率，研究了規則區域上helmholtz方程的fft快速演算法，以及有效地將多波前演算法引入計算電磁學領域用於求解差分稀疏矩陣方程。
  7. This one is complicated than the former. by using sparsity matrix technique and recursion, it can also be used in the larger system. the simulation system is constituted with matlab and the programs are formed with c language

    前者演算法結構簡單，便於編程實現，且計算速度快，主要適用於規模較小的系統；後者演算法結構較前者復雜，程序實現困難，但由於採用了稀疏矩陣技術，並用遞推法修正因子表，所以可以應用於規模較大的系統。
  8. 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。
  9. In the computation procedure of the above problems, efficient algorithms to perform sparse matrix were applied to saving computer memory units and cpu time. the conjugate gradient method and biconjugate gradient method were applied to solve the sparse systems of generated linear equations

    為了減少計算機內存的需求和有效提高計算速度，本文在分析計算各類目標的電磁散射和輻射問題時，採用稀疏矩陣的存儲和壓縮技術，並運用共扼梯度和雙共轆梯度等方法求解線性方程組。
  10. Based on the two - way cross list for storing sparse block matrices fast algorithm between block matrices and bandwidth optimization based on node reorder in sparse block matrices were conducted to reduce calculation complexity and memory capacity of the finite element analysis

    摘要在稀疏分塊矩陣的雙向正交鏈表存儲結構的基礎上，採用矩陣間的快速演算法和基於稀疏分塊矩陣的帶寬優化技術，減少了結構有限元分析的計算量和存儲容量。
  11. Based on work of w. clem karl etc., the quasi - newton iteration method for solving the optimization problem of sar imaging is derived, the sparse projection matrix tsof sar imaging is constructed, by replacing the original sar imaging projection matrix t with ts, the computation efficiency of peak - enhanced sar imaging is improved greatly

    在w . clemkarl等工作的基礎上，導出了求解峰值特徵增強sar成像優化問題的準牛頓迭代方法，建立了sar成像稀疏投影矩陣t _ s ，通過用t _ s代替原始sar成像投影矩陣了，有效提高了峰值特徵增強sar成像方法的計算效率。
  12. In this paper, we apply adi and high - order compact finite difference method for large - scale asymmetric sparse matrix in semiconductor device simulation

    摘要採用adi與高階緊致差分相結合的方法計算大型非對稱稀疏矩陣，並實現了該演算法在半導體器件模擬中的應用。
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