樣本空間 的英文怎麼說

中文拼音 [yàngběnkōngjiān]
樣本空間 英文
sample ace
  • 樣 : Ⅰ名詞1. （形狀） appearance; shape 2. （樣品） sample; model; pattern Ⅱ量詞（表示事物的種類） kind; type
  • 本 : i 名詞1 （草木的莖或根）stem or root of plants 2 （事物的根源）foundation; origin; basis 3 （本錢...
  • 空 : 空Ⅰ形容詞（不包含什麼; 裏面沒有東西或沒有內容; 不切實際的） empty; hollow; void Ⅱ名詞1 （天空） s...
  • 間 : 間Ⅰ名詞1 （中間） between; among 2 （一定的空間或時間里） with a definite time or space 3 （一間...
  • 樣本 : sample book; specimen; advanced copy; sample; muster; scantling; instance; statistics
  • 空間 : space; enclosure; room; blank; interspace
  1. A note on the method for constructing the confidence limits of parameters based on order relation in the sample space

    基於樣本空間中序關系構造參數置信限方法的一個注記
  2. It has the important influence on detection rate, false positive rate and ability of real time responds. so this thesis labors over kdd cup 99 intrusion detection data set and uses some rules to reduce the dimensions of feature sample space in the derection of sbg. thus the phenomena of dimension exploding can be avoided

    特徵提取是入侵檢測的關鍵，對檢測率、誤報率和實時性有著重要影響，因此本文在針對kddcup99入侵檢測數據進行了大量分析，並沿sbg的搜索方向，使用一定的規則集來達到特徵樣本空間的維數的削減的目的，從而避免了「維數爆炸」的現象。
  3. For the cooperation of pile - soil, the complicacy of the structure system and the design and calculation system of the pile foundation, and furth er more for it ' s difficult to determine the properties of various kinds of soil due to the large scope of samples, there are still some problems in real applications. by the way it seems there is no document or report about the reliability analysis of pile bucking at present

    結構可靠度設計是近年來才提出的基於概率論的設計方法，由於樁土共同工作，樁基的結構體系和設計計算體系十分復雜，各種土性的取值因為樣本空間的非常龐大而難以準確確定，因此離實際應用尚存在一定問題，而對基樁屈曲的可靠度分析目前似尚未見文獻報道。
  4. First, realized a wegener - willie distribute based network traffic anomaly detection algorithm. we make use of wegener - willie distribute to analyze the inherent time - frequency distribution characteristics of the traffic flow signal. then according to the experience of analysis on historical flow, we construct a normal flow training sample aggregation and a abnormal flow training sample aggregation

    通過魏格納-威利分佈分析網路流量信號在時頻分佈上所反映出的內在特點，根據歷史流量的經驗構造正常流量和異常流量兩個訓練樣本空間，通過k最近鄰分類演算法將帶檢測流量信號的時頻分佈與訓練樣本進行比較，完成對檢測樣本的自動分類識別。
  5. In connection with the difference and distribution characteristic of the samples in sample space rs based on dga, a new self - adapted weight fuzzy omean clustering model of fault diagnosis of the power transformer based on the potential function is proposed. meanwhile, from the aspect of geometry characteristic of fc - divided in s dimension sample space, a method is proposed for the purpose of getting an effective adjacent radius, adaptive cluster number c and original cluster center of x sample set. for the diagnosis sample x, the property measure and diagnosis rule are proposed, which under the condition of potential density function that determine c number of optimal fuzzy cluster p1

    根據以變壓器dga數據為特徵量的樣本空間各樣本差異特性以及樣本在空間r ~ s的分佈特性，首次提出了基於勢函數自適應加權的變壓器絕緣故障診斷的模糊c -均值聚類模型；同時，從s維樣本空間的f ~ c -劃分幾何特性出發，提出了一種求取樣本集的類勢有效鄰域半徑和自適應求取聚類數和聚類中心初值的方法；對一個待診斷樣本，設計了基於類勢密度函數意義下的屬性測度和診斷準則。
  6. Firstly, the paper, combining the characteristic of synchronous pulse bursts and inhibition with the modified pcnn model, presents a way of finding the foveation points in the images adaptively and effectively, and simulates the human vision system. secondly, pcnn is extended to pcnns, based on the properties of information couple and transmission, an algorithm that is used to fuse images of the same target got by several sensors to an image is presented to simulate the human vision system. thirdly, combining the properties of synchronous pulse bursts, capture, and transmission and competition of waves, the paper presents two ways of classification, one is an algorithm based on the properties of neuron to capture and inhibit to classify the data taking on any complex unlinear distribution robustly, the other is based on the restricted distance and modified of the former to remove the influence of inferior samples in classification ; fin ally, based on the accumulative difference pictures, and the forming and transmission of pcnn wave, selecting and controlling the direction of autowave by connecting the neighbouring neurons selectively, the paper presents a way to simulate the tracks of moving object and detect the moving direction

    首先結合pcnn的同步脈沖發放和側抑制特性，提出了基於改進型pcnn的圖像凹點檢測演算法，該演算法是一種自適應而有效的圖像凹點檢測方法，並且較好地模擬了人類視覺系統；然後，結合信息傳遞和信息耦合特性，將pcnn擴展成pcnns （ pcnn網路群） ，提出了一種基於pcnns的圖像融合演算法，能夠將多個傳感器獲取的同一目標的圖像信息融合到一幅圖像中，有效模擬了人類視覺系統；另外，結合pcnn的同步脈沖發放特性、捕獲特性和波的傳播競爭特性，開拓地將pcnn用於模式分類中，提出了基於耦合神經元點火捕獲抑制特性的分類方法和改進的約束距離下的pcnn分類方法，前者可實現對樣本空間中任意復雜分佈訓練樣本的穩健非線性分類，而後者能夠消除訓練樣本中刺點對分類的影響；最後，結合累積差分圖像思想、 pcnn波的形成與傳播特性，通過各神經元之間連接取向來選擇與控制自動波的流向，將pcnn用於運動視覺分析中的運動軌跡模擬及運動方向檢測。
  7. As for the undivided linear sample space, the kernel function is needed to map onto another high dimension linear space

    對于線性不可分的樣本空間，需要尋找核函數，將線性不可分的樣本集映射到另一個高維線性空間。
  8. In this paper, the notion of likelihood ratio, as a measure of deviation between a sequence of the arbitrary random variables and a sequence of independent random variables with different distributions, is introduced. a class of strong deviation theorems represented by inequalities are given on a subset of the sample space by constructing a negative supermartingale and using martingale convergence theorem

    本文通過引進似然比作為相依隨機變量序列相對于服從不同分佈的獨立隨機變量序列的偏差的一種度量，並通過構造一個非負上鞅，利用鞅收斂定理給出了樣本空間的一個子集上的一類用不等式表示的強偏差定理。
  9. The precision of the non - contact testing of flywheel gear ' s contour and location error of light electricity inspection machine based on virtual instrument has been carried on theory analysis in this paper. various contour and location tolerances of the part have been distributed depending on the result of the analysis, and the data handling method of measurement has been studied to find a data handling method of getting rid of the system error under one kind of condition of the big sample space

    本文對飛輪齒圈形位誤差光電檢驗機的精度進行了理論分析，依據分析的結果分配了零件的各種形位公差，並對測量結果的數據處理方法進行了研究，找到了一種在大樣本空間的條件下依概率排除系統誤差的數據處理方法，同時為了驗證其可靠度對其進行了計算機模擬實驗。
  10. Product sample space

    積樣本空間
  11. The method takes advantage of gray model acceptable for modeling of small samples to produce additional trained samples of network in the region of poor information and then uses anfis to train network again

    該方法利用灰色模型適用於小子樣建模的特點在樣本空間的貧信息區域插值生成附加網路訓練樣本，然後再由anfis重新訓練網路。
  12. We deeply discuss the importance of choosing sample sapce in two sides : one is the calculation of classical model of probability, the other is the independency of events, and the concept of probability should be fully used in the calculation of probability

    摘要從古典概型中事件概率的計算和事件的相互獨立性兩個方面，通過舉例較深入地分析了樣本空間選取的重要性，並指出在概率計算中要充分利用概率概念。
  13. After this, the data processing method and concepts about the stationarity and ergodicity of measurement system in the limited distance are proposed. this experimental system is proven to be limited stationarity and ergodicity in short distance sample space

    提出了測量系統在有限距離上的平穩和各態歷經性的概念和數據處理方法，證明了本實驗系統在短距離樣本空間具有有限平穩和各態歷經性質。
  14. Feedforward networks use back propagation algorithm to train a multi - layer network. after training, the multi - layer network can fit the function in the data space very well

    前向網路利用反向傳播演算法訓練多層網路，使訓練后的網路較好地擬合樣本空間中各點的函數值。
  15. On constructing and optimization of sample spaces in calculation of classical probability

    關于古典概率計算中樣本空間的構造及優化
  16. And find the reason that cause illusion is to choose the sample space wrongly, then explain the importance of choosing the sample space correctly

    並分析了導致錯覺的原因是錯誤地選擇了樣本空間，進而說明正確選擇樣本空間的重要性。
  17. In this dissertation, we propose improved genetic algorithm and utilize it to search sample space for classification and evaluation with the best representative subset of training set

    本文提出一種改進的遺傳演算法，利用改進的遺傳演算法搜索樣本空間，將得到的訓練集的近似最優代表性子集作為訓練集去分類評估集。
  18. Compared with conventional statistic classifier, the artificial neural network ( ann ) has been developed and applied to remote sensing data classification problem, which does n ' t need suppose parameterized distribution of sample space in advance

    與傳統統計方法的分類器相比較，人工神經網路法不需要預先假設樣本空間的參數化統計分佈，正在被越來越普遍的應用於遙感圖像分類的研究。
  19. Cc model utilizes super - circle to divide the example ' s space

    Cc模型採用超圓劃分樣本空間。
  20. It reduces the contrastive encrypted information swatch space which can be used, but it increases the difficulty to unlock

    同時由於減小了可用於對比的信息樣本空間，也增加了解密的難度。
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