change weights 中文意思是什麼
change weights
解釋
改變權值-
Compared with the classical bp algorithm, robust adaptive bp algorithm possesses some advantages as following : ( 1 ) increasing the accuracy of the network training by means of using both the relative and absolute residual to adjust the weight values ; ( 2 ) improve the robustness and the network convergence rate through combining with the robust statistic technique by way of judging the values of the samples " relative residual to establish the energy function so that can suppress the effect on network training because of the samples with high noise disturbances ; ( 3 ) prevent entrapping into the local minima area and obtain the global optimal result owing to setting the learning rate to be the function of the errors and the error gradients when network is trained. the learning rate of the weights update change with the error values of the network adaptively so that can easily get rid of the disadvantage of the classical bp algorithm that is liable to entrap into the local minima areas
與基本bp演算法相比，本文提出的魯棒自適應bp演算法具有以下優點： （ 1 ）與魯棒統計技術相結合，通過訓練樣本相對偏差的大小，確定不同訓練樣本對能量函數的貢獻，來抑制含高噪聲干擾樣本對網路訓練的不良影響，從而增強訓練的魯棒性，提高網路訓練的收斂速度； （ 2 ）採用相對偏差和絕對偏差兩種偏差形式對權值進行調整，提高了網路的訓練精度； （ 3 ）在採用梯度下降演算法對權值進行調整的基礎上，通過將學習速率設為訓練誤差及誤差梯度的特殊函數，使學習速率依賴于網路訓練時誤差瞬時的變化而自適應的改變，從而可以克服基本bp演算法容易陷入局部極小區域的弊端，使訓練過程能夠很快的「跳出」局部極小區域而達到全局最優。 -
In this dissertation, two kinds of optimization, methods are proposed. firstly, only these linking weights corresponding to the control rules that affect the control performance significantly are updated in order to reduce the compute works and speed up the training progress. secondly, the updating step is adjusted adaptively in accordance with the error and the change of error of the system based on the t - s model to get better performance
針對模糊神經網路控制器一般存在著在線權值調整計算量大、訓練時間長、過度修正權值可能導致系統劇烈振蕩等缺點，提出了兩種模糊神經網路控制器的優化方法：在線自學習過程中僅對控制性能影響大的控制規則相關的權值進行修正，以減小計算量，加快訓練速度；基於t - s模糊模型，根據偏差及偏差變化率大小動態自適應調節權值修正步長，抑制控制器輸出的劇烈變化，避免系統發生劇烈振蕩。 -
The delta rule algorithm always makes a change in weights, and it is based on activation as opposed to output
Delta規則演算法總是在權系數上調整，而且這是建立在相對輸出的激活方式上。 -
Through the characterization of the molecular weights of pam, sem and dsc of composite, the results clarified the change of mechanical properties of composites. the tensile strength and impact strength of pam2 / pa - 6 composite showed that were related to the content of initiator naoh for the polymerization of e - caprolactam. the intrinsic viscosity of pam, sem and the crystallinity of nylon phase carried out the results, which explained the change of mechanical properties of composites
對于pam2 pa - 6體系，復合材料的拉伸強度與沖擊強度隨醛胺摩爾比的變化趨勢與引發劑用量有關，通過pam2分子量、尼龍結晶度、球晶形態、 sem以及dsc等表徵方法對這種變化趨勢的研究表明，復合材料的力學性能與上述因素有密切的關系。 -
This paper studies a design method of decentralized signal detection system which consists of adaptive fuzzied local - detectors and a data fusion rule of on - line self - learning weights. the local - detectors for inaccurate signal parameters are modeled by means of fuzzy sets which can be adapted to change of the inaccurate signal parameteres. the data fusion center where the optimal declsion rules are used as objective function can learn the local decision weights on - line. the robustness of the fuzzied local - detectors and the adaptability of the self - learned fusion rule make it true that the detection performance of the decentralized detection system is improved under uncertainty and this system can also process the decentralized signal detection with a unknown parameter of unknown distribution or non - random unknown parameter
本文研究了一種由局部自適應模糊檢測器和在線自學習融合演算法所構成的分散式信號檢測系統的設計方法.由模糊集對不精確信號參數的局部檢測器進行建模，該模糊模型可自適應不精確信號參數的變化.融合中心以最佳融合規則作為目標函數在線自學習局部判決的權重.局部模糊檢測器的魯棒性和自學習融合演算法的自適應性使該分散式檢測系統在不確定環境下的檢測性能得到提高.也使該系統能夠處理未知分佈的未知參數以及非隨機未知參數的分散式信號檢測 -
We modeled the controlled chaotic systems in neural networks with linear outputs. based on lyapunov theory and control methods of nonlinear systems, the change law of weights of neural networks and a nonlinear feedback controller are designed. the scalar output of the model can synchronize the given scalar chaotic signal
該方法通過坐標變換，利用線性輸出神經網路構造被控混沌系統的模型，並基於lyapunov理論與非線性系統控制方法，設計出神經網路權值變化規律與非線性反饋控制器，使神經網路模型的標量輸出能大范圍同步于給定的摘要標量混沖信號。 -
Lpa with higher molecular weights needs lower concentration to obtain co - continuous structure. however, for the sample with polystyrene based lpa, the morphology had little change with the increase of lpa concentration
分子量較高的lpa只需要較低的濃度就能夠形成交互連續的兩相結構，而聚苯乙烯類lpa試樣，固化形態隨著濃度增加沒有明顯的改變。 -
The essence of back propagation networks is that make the change of weights become little by gradient descent method and finally attain the minimal error
其實質是採用梯度下降法使權值的改變總是朝著誤差變小的方向改進，最終達到最小誤差。 -
However, in children with birth weights of less than 1000 g, there was no significant change in the prevalence over the 17 - year study period
然而，在出生時體重不足1000克的患兒中， 17年間發病率卻沒有顯著的變化。
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