軌跡消除器 的英文怎麼說

中文拼音 [guǐjīxiāochúqì]
軌跡消除器 英文
track eradicator
  • 軌 : Ⅰ名詞1. （路軌;軌道） rail; track 2. （比喻辦法、規矩、秩序等） rut; path; course Ⅱ動詞[書面語] （遵循; 依循） follow
  • 跡 : 名詞1 （留下的印子; 痕跡） mark; trace 2 （前人遺留的建築或器物等） remains; ruins; vestige 3 （...
  • 消 : 動詞1 （消失） disappear; vanish 2 （使消失; 消除） eliminate; dispel; remove 3 （度過; 消遣） pa...
  • 除 : Ⅰ動詞1 （去掉） get rid of; eliminate; remove 2 [數學] （用一個數把另一個數分成若干等份） divide:...
  • 器 : 名詞1. （器具） implement; utensil; ware 2. （器官） organ 3. （度量; 才能） capacity; talent 4. （姓氏） a surname
  • 軌跡 : 1 [數學] （某點在空間移動的路線） locus; trajectory; trail; travel; path; way; [電子學] trace; li...
  • 消除 : eliminate; dispel; remove; clear up; wipe off
  1. 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。
  2. As neural network has the ability of self - learning, that utilizes prior output data of uncertain system to estimate iteratively the static state property of system in order to achieve ideal approaching precision for identification of the positive model, a robust iterative learning control scheme on the basis of better positive model is designed. the neural network is used to identify the positive model of nonlinear system on iterative axis, which can give feed - forward action of iterative learning controller to reduce the effects of nonlinear properties and model uncertainties. meanwhile, feedback action of iterative learning controller make joint movement follow the desired trajectory on time axis by using controlled parameters derived by the neural network

    由於神經網路具有自學習能力，它可利用不確定性系統的歷史輸出數據對系統的穩態特性進行估計，使得對系統正向模型的辨識達到理想的逼近精度，然後在此正向模型的基礎上進行學習控制律的設計：即採用神經網路辨識非線性系統的正向模型，並消除系統不確定性和外部干擾的影響，使關節運動沿迭代軸方向逼近期望軌跡；迭代學習控制器在線學習控制參量，使關節運動沿時間軸方向跟蹤期望軌跡。
  3. In this thesis, i built the mathematical model of 2r robot firstly, and designed the robot follow track pid control system. it could eliminate effectively the system static error

    文中首先建立了兩關節機器人的數學模型，並構造了機器人軌跡跟蹤的pid控制系統，它能有效的消除系統的穩態誤差。
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