perceptron 中文意思是什麼

perceptron 解釋
n. 名詞 【無線電】視感控器〈類似視神經的電子儀器〉。

  1. Based on analyzing the multilayer perceptron neural network, it induces the error backpropagation algorithm while taking the hyperboloid tangential function as nonlinear activation function

    在分析多層感知器神經網路的基礎上，推導了雙曲正切函數為激勵函數的誤差後向傳播演算法。
  2. Is that if a set of points in n - space is cut by a hyperplane, then the application of the perceptron training algorithm will eventually result in a weight distribution that defines a tlu whose hyperplane makes the wanted cut

    ）下的結論是，如果n維空間的點集被超平面切割，那麼感知器的培訓演算法的應用將會最終導致權系數的分配，從而定義了一個tlu ，它的超平面會進行需要的分割。
  3. Perceptron as feature detector. visual receptive fields

    做為特徵探測器的感應機。視覺的接受域。
  4. A pavement performance predicting method on the fuzzy perceptron

    基於模糊感知器的路面性能預測方法
  5. There are important differences from the perceptron algorithm

    這里有一些與感知器演算法相區別的重要不同點。
  6. Approach to rule extraction and generation using rough multilayer perceptron networks

    網路的規則提取及生成方法研究
  7. Perceptron learning rule

    感知器學習規則
  8. Visual kernel perceptron

    視覺核感知器
  9. For an implementation of the perceptron with a gui, see

    關于包含圖形界面的感知器的執行，請參閱omri weisman和ziv pollack撰寫的
  10. 4. algebra hyper surface neutral network is a kind of expanded perceptron model

    重點研究了一類感知器推廣模型? ?代數超曲面神經網路模型。
  11. Nevertheless it cannot be easily minimized by most existing perceptron learning algorithms

    然而，現有的感知器學習演演算法無法輕易的對這個函數最佳化。
  12. Neural network is deeply researched as representation of eager classification. perceptron is selected

    選取神經網路分類演算法作為急切分類演算法的代表進行深入的研究。
  13. Based on rbf neural network and perceptron neural network, a four - layer feed - forward neural network named radial basis perceptron ( rbp ) network is presented

    基於rbf網路和感知器（ perceptron ）網路建立一四層前饋神經網路?徑向基感知器（ radialbasisperceptron ， rbp ）網路。
  14. The perceptron 3d scanning solutions group is dedicated to providing high value software and sensor based 3d scanning solutions for new perceptron clients in industries such as automotive, aerospace, and steel

    感知三維掃描解組，是專門用來提供高價值的軟體和傳感器的三維掃描解新的感知客戶的行業，如汽車，航空，鋼鐵等
  15. For short - time natural gas load forecasting. based on analyzing tech situation at home and abroad, considering all kinds of factors which will have influence on load changes, a hybrid approach combined the self - organizing feature map ( sofm ) neural network with multilayer perceptron ( mlp ) is presented, and short - time load forecasting model is established

    針對大然氣短期負荷預測的問題，在分析了國內外技術現狀的基礎上，綜合考慮影響負荷變化的各種因素，提出了基於白織織競爭網路和多層感知機網路棍合的大然氣短期負荷預測方法。
  16. The continually optimized connecting relation is gained via perceptron and xor function, then the optimal path graph is found

    利用感知器異或函數獲得了節點之間不斷優化的連接關系，然後得到最優路徑圖。
  17. Two spatially registered images with different focuses are decomposed into several blocks. then, three features reflecting the clear level of every block, i. e., spatial frequency, visibility, and edge, are calculated. finally, artificial neural networks, i. e., multilayer - perceptron, radial - basis function, probabilistic neural network, are used to recognize the clear level of the corresponding blocks to decide which blocks should be used to construct the fusion result

    具體實現過程概述如下：首先將兩幅（或多幅）配準圖象進行分塊處理，提取兩幅圖象中對應塊的能反映圖象清晰度的三種特徵，即空間頻率、可見度和邊緣，將特徵歸一化後送入訓練好的神經網路進行識別，根據得到的結果依據「誰清晰誰保留」的原則構成融合的圖象。
  18. This paper aims to combine advantages of pid control and neuron, propose the neuron pid controller which is derived from an incomplete derivative pid algorithm and based on six learning rules in common use, viz. no surpervized hebbian learning rule, perceptron learning rule, supervized learning rule, improved hebbian learing rule, delta learning rule and capability index which is based on second type, and these rules come into being six control arithmatic. then simulate in object with lag

    本論文主要將兩者的優點結合，提出了神經元實現不完全微分pid ，並採用神經網路常用的六種學習規則，即無監督hebb學習規則、感知器的學習規則、有監督的hebb學習規則、改進的hebb學習規則、 delta學習規則和基於二次型性能指標的學習規則，形成六種控制演算法，以工業生產過程中常見的二階純滯后對象為例進行模擬。
  19. The problem of credit assignment. perceptron learning rule. convergence theorem. ? learning by gradient following. online learning

    原因探究、感應機學習規則、收斂定理。梯度跟隨學習法、線上學習。
  20. This paper begins with the restrictions of the - existent net - flow modelling methods. integrated with the characteristics of modern net - flow system and utilizing francesco luna ' s idea of pcrceptron and xor function, we express human ' s consciousness with logistic function of perceptron, and the uncertain relations among nodes are mapped to xor function. on the basis of these, a new modelling method of net - flow is offered

    本文從已有網流系統建模方法的局限性出發，結合現代網流系統的特徵，利用francescoluna的感知器與異或問題的思想，將人的意識用感知器對應的邏輯函數進行描述，節點之間連接關系的不可感知性映象為異或函數，提出網流系統的一種新的建模方法。
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