非競爭型抑制 的英文怎麼說

中文拼音 [fēijìngzhēngxíngzhì]
非競爭型抑制 英文
uncompetitive inhibition
  • : Ⅰ名詞1 (錯誤) mistake; wrong; errors 2 (指非洲) short for africa 3 (姓氏) a surname Ⅱ動詞1 ...
  • : 動詞(競爭; 競賽) compete; contest; vie Ⅱ形容詞[書面語] (強勁) strong; powerful
  • : Ⅰ動詞1 (力求得到或達到; 爭奪) contend; vie; compete; struggle for; strive 2 (爭執; 爭論) argu...
  • : Ⅰ動詞(向下按; 壓制) restrain; repress; curb Ⅱ連詞[書面語]1 (表示抉擇) or 2 (表示轉折) but3 ...
  • : Ⅰ動詞1 (製造) make; manufacture 2 (擬訂; 規定) draw up; establish 3 (用強力約束; 限定; 管束...
  • 競爭 : compete; vie; contend
  • 抑制 : 1 (控制) restrain; control; check; hold up; curb; stop; repress; bridle; choke; prehension; sup...
  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特性,提出了基於改進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。
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