模式分類 的英文怎麼說

中文拼音 [móshìfēnlèi]
模式分類 英文
pattern classification
  • 模 : 模名詞1. （模子） mould; pattern; matrix 2. （姓氏） a surname
  • 式 : 名詞1 （樣式） type; style 2 （格式） pattern; form 3 （儀式; 典禮） ceremony; ritual 4 （自然科...
  • 分 : 分Ⅰ名詞1. （成分） component 2. （職責和權利的限度） what is within one's duty or rights Ⅱ同 「份」Ⅲ動詞[書面語] （料想） judge
  • 類 : Ⅰ名1 （許多相似或相同的事物的綜合; 種類） class; category; kind; type 2 （姓氏） a surname Ⅱ動詞...
  • 模式 : model; mode; pattern; type; schema
  1. Immune evolutionary algorithms are optimal algorithms in essence, therefore, they can be used in some fields, such as cybernation, pattern recognition, optimal design, meshing learning, network security, etc. there are also some examples of these attempts described in this paper

    免疫進化計算在本質上講是一種優化演算法，所以它們可以應用於一些諸如自動控制、故障診斷、模式分類、圖象識別、優化設計、機器學習和網路安全性等廣泛領域，本文在這方面也做了一些初步的嘗試。
  2. Firstly the patterns of the multifingered hands are detailed, eight patterns are defined. the classical bayes method is used in the classification of pre - grasp of multiple fingers based on three patterns which are grasping, holding and pinching. based on the eight pre - grasp patterns, bp neural network is applied in the classification of the pre - grasp of multifingered hands and gets a good effect. the method solves the shortcoming input sample relying on the propobility density and simplified the un - insititution characters extraction. in this paper, support vector machine ( svm ) and binary - tree with clustering is applied in the classification. this method can solve the slow speed and effect with fewness sample in the classification, achieving a good effect. in this papper, we extract the characters of the regulation object with geometry characters and extact the unregulation object with the image analysis

    此法解決了輸入樣本依賴物體的概率密度的特點，簡化了分類特徵提取的不直觀性。本文還採用了支持向量機（ svm ）和聚類二叉樹相結合的方法對機器人手預抓取八類模式進行分類，解決了預抓取模式分類訓練速度過慢以及在分類中樣本數量偏少而影響分類效果的問題，得到了較高的正確率。本文對預抓取幾何形狀規則的物體採用直接提取其幾何特徵，對于預抓取幾何形狀不規則的物體採用圖像分析的方法進行特徵提取。
  3. Some open testing datasets and real gene microarray data are applied in experiments. the results have verified the feasibility and validity of the pica to get the gene microarray data and the advanced boosting algorithm for gene classification

    經過對公開的測試數據集和真實的基因微陣列數據大量實驗，證明了用部分獨立分量分析方法獲取基因微陣列數據及boosting改進演算法進行基因模式分類的可行性和有效性，最終也完成了基因模式的識別任務。
  4. By using the optimized covariance matrices to optimize the new regularized discriminant analysis ( rda ), the correct classification rate is higher than that by the old rda

    利用優化的協方差矩陣對正則化判別分析方法進行優化，其模式分類正確率有顯著提高。
  5. Though the method has generalization capability, it doesn ’ t satisfy the application. when the examples include yawp, wrong recognition occurs. generalization of the traditional is not ideality and instability

    神經網路模式分類方法雖然具有比其他分類方法更好的泛化能力，但在實際應用中，仍然不能滿足人們的期望。
  6. The new feature derived from the multiple features fusion benefits from the advantage of single feature to the pattern classifying, which is superior to each fused feature on terms of the classifying performance

    由多個特徵融合產生的新特徵吸收了單個特徵的對模式分類的優勢，使它對模式的分類性能優于參與融合的單個特徵。
  7. Fingerprint classification based on direction image

    基於方向圖的指紋模式分類研究
  8. In order to deal with the unknown transformations of samples as a result of preprocessing and improve the system recognition performance further, a palmprint feature extraction method based on template learning in wavelet domain is designed and proposed. this algorithm learns the ideal templates of different classes from palmprint samples, whose parameters are regarded as

    該演算法從掌紋樣本中學習不同類別的理想模板，並將理想模板的參數作為特徵用於模式分類，由於考慮了子圖樣本內在存在的平移和旋轉變換，不同類型小波系數對特徵提取的貢獻，因此達到非常好的識別效果。
  9. 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。
  10. Power system fault diagnosis can be described as a mode classified problem, and it is quite fit to apply the decision table method of rough sets theory

    電網故障診斷可以用一個模式分類問題來描述，很適合應用粗糙集（ rs ）理論的決策表方法。
  11. In the following virtual memory management subsystem design, after analyzing the hardware - software dividing line and cooperation in detail, four key issues of virtual memory manage subsystem design are discussed : the classification of processor operating mode, the partition of virtual space, the access controlling and the design of control coprocessor ( ccop ). a virtual manage subsystem prototype is then presented

    在虛存管理子系統設計的討論中，詳細分析了虛存管理中軟硬體的分工協作，深入研究並解決了虛存管理子系統設計的四個核心問題：處理器工作模式分類、虛地址空間劃分、訪問控制和控制協處理器設計，並在此基礎上給出了一個虛存管理子系統原型。
  12. Because the structure is simple, pnn is an effective model for many classification problems and many pattern recognitions

    Pnn的拓撲結構簡單，容易設計演算法，廣泛應用於模式識別及模式分類領域
  13. According to the requirements to pd pattern auto - recognition, this paper studies systematically the basic theories and realizable methods for auto - recognition of pd gray intensity image : ( 1 ) in the requirement of on - line pd monitoring for transformer, several discharge models are designed and the relevant experiment methods projected. with discharge model tests, a lot of discharge sample data is acquired. on the base of systematical research on recognition for pd gray intensity image, this paper puts forward two kinds of fractal features, the 2nd generalized dimensions of original pd images and fractal dimensions of high gray intensity pd images, and then the relevant extraction methods

    針對局部放電模式自動識別的需要，作者系統地研究了局部放電灰度圖像自動識別中的基本理論和實現方法： （ 1 ）根據變壓器局部放電在線監測的要求，設計了放電模型和實驗方法，並通過模型實驗獲得了大量放電樣本數據，為構造局部放電灰度圖像和採用bpnn進行識別作好準備； （ 2 ）研究了局部放電灰度圖像的構造方法以及降維構造32 32灰度和矩陣的方法；在用人工神經網路對局部放電進行模式識別時，分析了bp網路的優缺點，對典型bp網路的結構和學習訓練演算法提出了改進，採用帶有偏差單元的遞歸神經網路作為模式分類器；採用32 32灰度和矩陣進行bpnn識別結果表明這種方法是有效的。
  14. Classified exploration of west moral education patterns in present - day

    當代西方道德教育模式分類探索
  15. Study of surface emg pattern classification based on bayes decision technique

    決策理論的表面肌電信號模式分類的研究
  16. At present support vector machine has found applications in model classification

    摘要目前支持向量機在模式分類中得到了很好的應用。
  17. The feature extraction and pattern recognition are introduced in structural damage identification

    研究了結構損傷識別中的特徵提取和模式分類方法。
  18. Pattern classification of flaw was carried out with bp neural network and the feature selected

    利用bp神經網路分類器及選擇的特徵值對缺陷進行模式分類。
  19. The pattern recognition results prove that the kiii network is a good pattern classifier

    由模式識別的實驗結果看出， k網路是一種較好的模式分類方法。
  20. Pattern classification of flaw is carried out with bp neural network and the feature selected

    利用bp神經網路分類器及選擇的特徵值對缺陷進行了模式分類。
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