linear mapping 中文意思是什麼
linear mapping
解釋
線性映假象-
This paper concerns with almost all kinds of generators such as the linear, nonlinear and inversive congruential methods, fibonacci and tausworthe sequences, add - with - carry and subtract - with - borrow methods, multiple prime generator and chaotic mapping
目前國際上關于隨機數有很多熱門的理論和方法，除了傳統的線性同余法，還有非線性同余法、 fibonacci 、 tausworthe序列、進位加?借位減發生器法等。 -
Thirdly, from the idea of locally linear approximate, another tangent - plane algorithm is presented for the distance between the convex nurbs surfaces. the critical step is the construction of the support mapping by gjk and lc to search for nearest points, and emphases are laid on dealing with isotropic cases and choosing initial iterated points. it is also proved that no isotropism during iteration would take place if initial iterated points are positive points
切平面法是運用gjk和lc構造支撐映射的原理而設計的一個搜索近點對的迭代法，著重給出了迷向情況的處理和初始迭代點的選取方法，並證明了只要將初始迭代點取為陽點，就不會出現迷向情況。 -
Based on this kind of relations between the topological structures and the content distributions we study the web modelling, community identification and some related application problems in detail : first, after some existed characteristics of the web topology are verified, some new characteristics are discovered : the high clustering property in micro - topology ( high average gathering coefficient ), the obvious mapping relation between the topological struture and the content in micro - level 、 linear irrelevant between the degree distribution of network nodes and the relative degree distribution of contents etc. then after analysis the topology of the complex network and the network modeling, the muti - scale determinism is proposed, especially for the information network a web evolvement model ( prcp model ) that fused the node authority and the node correlation is proposed. the model deduction, evolving learning verification and large scale experiment proof indicate that the model can explain the micro - topology centralizing phenomena, can imitate the mapping relation between the network connecting distribution and network content relative distribution and also can predict the mapping relation between the topology clustering and content clustering
本文在詳細觀察了web網路的拓撲結構特徵以及拓撲結構與內容分佈相互關系的基礎上，以信息網路的物理連接拓撲結構與節點內容相關度分佈之間的相互關系為主線，從網路特徵、網路建模、社區分析及相關應用方面問題進行了深入細致地探討:首先在驗證了前人提出的web網路拓撲結構特徵基礎上，進一步發現了信息網路所具有的一些新特徵: 1 ）網路微觀顆粒度的拓撲結構聚團與內容聚團存在明顯的映射關系，具體包括節點之間的物理連邊概率與節點之間的內容相關度成指數比例關系、節點形成三角形拓撲結構的概率與節點內容相關緊密程度之間同樣具有一種指數比例關系; 2 ）網路節點連接度整體分佈與節點內容相關度整體分佈是線性無關的; 3 ）網路微觀拓撲結構中的存在很強的集聚性（平均聚團系數很高） 。 -
In this thesis, based on item response theory, a number of ways to estimate the latent trait and item parameters were introduced and their advantages and disadvantages were analyzed ; what is more, empirical logistic regression and two parameters logistic model ( 2plm ) are combined to set up a linear model by logit - mapping and a new parameter - estimation method is proposed
新方法將經驗logistic回歸用於兩參數logistic模型的參數估計，使用logit變換建立線性模型，利用線性模型的最小二乘估計得到第j個項目的項目參數向量_ j = （ _ j ， _ j ）的兩步估計由於x _ j含有未知的討厭參數，的理論值也和有關，我們結合上式的結果對進行再估計。 -
Monte carlo simulations were conducted to study the new approaches of qtl mapping, the results indicated that general least squares ( gls ) method, which was widely applied in mixed linear model, could unbiasedly estimate all genetic main effects, including additive effects, dominance effects and epistatic effects of additive by additive, additive by dominance, dominance by additive, dominance by dominance. the interaction effects between genetic main effects and environments could also be predicted unbiasedly by linear unbiased prediction ( lup ). the heterosis prediction based on qtl effects was also unbiased
對新提出的qtl分析方法進行了montecarlo模擬研究，結果表明，廣泛應用於混合線性模型的廣義最小二乘法（ gls ）能夠無偏估計加性效應，顯性效應以及加加、加顯、顯加、顯顯上位性效應等各項遺傳主效應；運用線性無偏預測法（ lup ）能夠無偏預測上述各項遺傳主效應與環境的互作效應；基於qtl效應的雜種優勢預測也是無偏的。 -
A new temperature segmentation linear fitting method sieves the problem caused by the nonlinear mapping between the temperature data and the chroma. that is dividing the temperature into some sections from high to low. different temperature section uses different formula
提出了一種新的溫度分段線性化擬合方法解決溫度數據與色度的非線性映射問題，即將火焰溫度由高向低分成幾個溫度段，不同的溫度段使用不同的運算公式，從而提高了測量的精度，避免了過去方法中試圖用一個標定試驗的公式來求解跨度較大的整個溫度場分佈時所產生的誤差。 -
Almost linear mapping
殆線性映射 -
The engine controller is in fact a multi - dimensional, complicated non - linear mapping device of the inputs and outputs. therefore with the ability of mapping non - linear and complex functions, the multi - layer forward neural network can be used to establish these relationships based on the experimental data
發動機控制器實際上就是一個多維的、復雜的傳感器輸入與控制量輸出的非線性映射裝置，因此，可以利用多層前向網路所具有的映射復雜非線性函數的性能，在大量數據的基礎上建立起該映射關系。 -
This paper confirms a kind of non - linear mapping relation between vibration velocity of particles on building and the influence factors, such as total explosive charge, maximum explosive charge fired at the same time, the distance between blasting point and monitoring points, peak particle velocity of ground where building is, the height from monitoring point to ground, and so on, and sets up a support vector machine ( svm ) model for forecasting the vibration effect induced by an explosion
應用支持向量機，建立了總藥量、最大段藥量、爆破點與監測點距離、構築物所在地面震動峰值速度、測點到地面的高度等因素與建築物上的質點震動速度之間的非線性映射關系，確立了支持向量機預測模型。 -
Positive linear mapping
正線性映射 -
Some properties of the unit - preserving linear mapping between banach algebras
代數之間保單位線性映射的若干性質 -
Regular linear mapping
正則線性映射 -
A non - linear mapping method for reducing the transmitted signals amplitude peak in multicarrier system
系統發送信號峰值的非線性映射方法 -
Samples show that this method is effective for the condenser fault diagnosis. the condenser fault diagnosis is a complicated non - linear mapping
本文首次嘗試用決策樹方法對凝汽器故障進行診斷，研究結果表明，該方法切實可行。 -
Neural network technique is adapted well to the fem correction for its strong non - linear mapping ability rapid computation and anti - interference capability
神經網路方法因其具有非線性映射能力強、計算速度快、容錯性好等優點，非常適合於結構有限元模型修正。 -
Bp ( back propagation ) algorithm is the most popular training algorithm in applications for its non - linear mapping approach capability and robustness. however, it has some defects, such as converging slowly and immersing in local vibration frequently
Bp演算法以其良好的非線性映射逼近能力和泛化能力以及易實現性成為人工神經網路應用最廣泛的訓練演算法，但是bp演算法也有其明顯的缺陷，即訓練速度慢、容易陷入局部極值等。 -
Artificial neural network ( ann ) is non - linear technology developed since 1980. the ann model is determined by topology structure, activation function and learning method. the model possesses with good fault tolerance, self - adaptability and non - linear mapping, especially it is suitable to resolve complex causal problems
人工神經網路模型具有很強的容錯性、自適應性和非線性的映射能力，特別適于解決因果關系復雜的非確定性推理、判斷、識別和分類等問題。 -
Secondly, a non - linear mapping function from multiple inputs ( design variables ) to output ( maximum dynamic stress ) is constructed within bp neural networks, in order to obtain the constraint function values that are necessary in optimum design of structures using genetic algorithms and get the optimum solutions. the generation ability of the bp network after training can be used to replace the calculation of fem, which makes the constrained optimization to be possible
其次，由於動應力的有限元法計算過程復雜，計算量巨大，在應用優化演算法時，需要反復計算，為了使優化過程可行，設計了bp神經網路，利用有限元計算的樣本數據建立起結構設計參數（輸入）與動應力（輸出）的非線性映射關系，從而代替有限元法，快速計算結構動應力。 -
2. on the base of detailedly analysing the fourier neural networks, we find this neural networks have the characteristic which can transform the nonlinear mapping into linear mapping. so, we improve the original learning algorithm based on nonlinear optimization and propose a novel learning algorithm based on linear optimization ( this dissertation adopts the least squares method ). the novel learning algorithm highly improve convergence speed and avoid local minima problem. because of adopting the least squares method, when the training output samples were affected by white noise, this algorithm have good denoising function
在詳細分析已有的傅立葉神經網路的基礎上，發現傅立葉神經網路具有將非線性映射轉化成線性映射的特點，基於這個特點，對該神經網路原有的基於非線性優化的學習演算法進行了改進，提出了基於線性優化方法（本文採用最小二乘法）的學習演算法，大大提高了神經網路的收斂速度並避免了局部極小問題；由於採用了最小二乘方法，當用來訓練傅立葉神經網路的訓練輸出樣本受白噪聲影響時，本學習演算法具有良好的降低噪聲影響的功能。 -
The neural network technique has shown great superiority in structural damage diagnosis for its strong non - linear mapping ability, rapid computation and anti - interference capability
神經網路方法因其具有非線性映射能力強、計算速度快、容錯性好等優點，非常適合於結構損傷診斷領域。
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