sparseness 中文意思是什麼
sparseness
解釋
稀疏-
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。 -
What we show in this paper ( the second part ) is that although the sparseness of the contingency table is an aspect that would affect the power of j ^, the affect of the weight is also important and should not be ignored
為了改進檢驗的效果，本文通過給tmhet的各項以合理的不同的權而得到一個新的加權統計量，並且比較了兩者的功效。 -
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。 -
This paper present the classic backtracking as an example, through comparing, explains backtracking efficiency difference under various data structure ; when database can be expressed in sparseness matrix, then it can be expressed in 4 - way linked list, which improves greatly the efficiency than before
以一個典型的回溯問題為例，通過對比，說明回溯法在不同數據結構下，其時間效率的差異，驗證對于可表示成稀疏矩陣的數據集，在使用四向鏈表結構時，可以大大提高時間效率。 -
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。 -
Upon the dawn of the 21st century, the social and economic system with companies as its core is facing dramatic changes, the main feature of which is the emerging of organizations characterized by it, knowledge accumulation and sharing, as well as the shift of sparseness among various resources
在人類邁入21世紀時，以企業為核心的社會經濟系統正面臨著一個巨大的飛躍。其基本標志就是信息技術、知識積累和知識共享為特徵的組織的興起，各種資源的稀缺性發生了相對轉移，進而對原有的企業內在和外在的框架提出了挑戰。 -
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。 -
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。 -
For the sake of sparseness of edge pixels, the matching area may big enough to find an accurate corresponding edge pixel
由於邊緣點的稀疏，匹配時選用的區域可以大些，可以得到準確的匹配點。 -
The relative frequency training ( rft ) method is used to estimate the model parameters. and the problem of the data sparseness is solved through the backing off data smoothing algorithm
同時採用了回退式參數平滑演算法來解決了一階隱馬爾可夫模型的數據稀疏問題。 -
The node force corresponding to damp was used to control the mesh distortion. numerical studies show that the method proposed by this paper can successfully control the severe distortion of mesh and retain the density of elements during the membrane form - finding when the damp viscosity coefficient is in a limited scale. especially this method can avoid the sparseness of mesh in the location of lower curvature and have good convergence characteristic
同時針對找形分析中的動力鬆弛格式，本文提出了全新的控制網格變形的動力鬆弛法，此方法能夠有效地解決膜結構找形分析中網格的大變形問題，克服了在曲率較小處網格過于稀疏的缺陷，在曲率較小處保證了單元的密度和初始構形的精度，並且收斂性較好，為準確進行荷載分析和裁剪分析奠定了基礎。 -
Another corner is set up as a hakka peasant family s dwelling, the sparseness of the furnishings reflects the hakka people s frugal life style
展場的另一角介紹客家人的農耕生活，村屋內簡樸的陳設充分反映客家人艱苦檢樸的生活。 -
The holistic features are extracted by principal component analysis ( pca ), and the local features are extracted by non - negative matrix factorization with sparseness constraints ( nmfs )
首先通過主元分析演算法（ pca ）提取全局特徵，利用帶稀疏限制的非負矩陣分解演算法（ nmfs ）提取局部特徵。 -
In this thesis, we mainly use snmf ( sparse nonnegative matrix factorization ) as the method of rank reduction, which extend the nmf to include the option to control sparseness explicitly
本文主要採用snmf （非負稀疏矩陣分解）演算法作為降維和提取特徵向量的工具，該演算法是在nmf演算法的基礎上加上顯式地稀疏因子控制而形成的一種非負矩陣分解方法。 -
This method effectively shield the learning process from plenty of feedback noises produced by distorted threshold and sparseness of initial information, and also imitate artificial feedback approximately to perfect the intelligence of adaptive learning mechanism
此外，選擇聚類擇優后的一類信息參與rocchio自適應學習與更新，能夠有效地削弱閾值偏見性和偽相關反饋排序偏見性造成的負面影響。 -
Principle component analysis ( pca ), as a classical method for feature extraction, learns holistic representations of facial images, while non - negative matrix factorization ( nmf ), a recently proposed approach, learns parts - based representations of faces. however, we argue that nmf can not only learn parts - based representations but also holistic ones with different sparseness constraints
在眾多的特徵提取演算法中，基於全局特徵提取的主元成分分析（ principlecomponentanalysis ， pca ）是討論最多的經典演算法，與此對應的是基於局部特徵提取的非負矩陣分解（ non - negativematrixfactorization ， nmf ）演算法。 -
In this thesis, we propose an efficient nmfs + rbf aggregate framework for fr, in which non - negative matrix factorization with sparseness constraints ( nmfs ) is firstly applied to learn either the holistic representations or the parts - based ones by constraining the sparseness of the basis images, and then the rbf classifier is adopted for pattern classification
本文提出了一種基於非負矩陣稀疏分解（ non - negativematrixfactorizationwithsparsenessconstraints ， nmfs ）和rbf神經網路的人臉識別方法。通過控制稀疏度， nmfs演算法既可提取人臉全局也能提取局部特徵，再運用rbf神經網路進行模式分類。
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