誤差反傳演算法 的英文怎麼說

中文拼音 [wùchāfǎnzhuànyǎnsuànfǎ]
誤差反傳演算法 英文
error back propagation algorithm
  • 誤 : Ⅰ名詞（錯誤） mistake; error Ⅱ動詞1 （弄錯） mistake; misunderstand 2 （耽誤） miss 3 （使受損害...
  • 差 : 差Ⅰ名詞1 （不相同; 不相合） difference; dissimilarity 2 （差錯） mistake 3 [數學] （差數） differ...
  • 反 : Ⅰ名詞1 （方向相背） reverse side 2 （造反） rebellion 3 （指反革命、反動派） counterrevolutionari...
  • 傳 : 傳名詞1 （解釋經文的著作） commentaries on classics 2 （傳記） biography 3 （敘述歷史故事的作品）...
  • 演 : 動詞1 （演變; 演化） develop; evolve 2 （發揮） deduce; elaborate 3 （依照程式練習或計算） drill;...
  • 算 : Ⅰ動詞1 （計算數目） calculate; reckon; compute; figure 2 （計算進去） include; count 3 （謀劃;計...
  • 法 : Ⅰ名詞1 （由國家制定或認可的行為規則的總稱） law 2 （方法; 方式） way; method; mode; means 3 （標...
  • 誤差 : error
  1. Applying the classical pattern recogtiition theory anci ftiflcial neural networks method, this paper proposes the analog fault diahoes priricip1s with backward - propagation neural network ( i3pnn ) arid self - or ~ anizing feature map ( sofm ) neural network algorithm implementation

    本文提出了模擬電路故障診斷前向多層誤差反傳（ bp ）網路和自組織特徵映射（ sofm ）網路的演算法實現方法。
  2. On the basis of analysing multilayer forward artificial neural networks which based on back propagation algorithms and basic principles of the adaptive noise cancellation system, this paper sets up an adaptive noise cancellation controller based on artificial neural network, which is proved to be more efficient in the noise cancellation and has robust performance based on simulink of matlab at the end, this paper proposes some advices of model and algorithms

    在對基於誤差反向傳播學習演算法的多層前向人工神經網路進行分析基礎上，結合傳統自適應噪聲抵消系統基本原理，建立了基於人工神經網路的自適應噪聲抵消器，經基於matlab的simulink模擬實例證明，具有很強的噪聲濾除能力和魯棒性。最後並提出了網路及演算法進一步改進的方法。
  3. Specific issues examined are : compensation for the variation of the stator resistance, the offset error of the dc bus voltage, the voltage error generated by the forward voltage drop the dead time of the switches, improvement of the steady state performance, and the speed sensorless control for the pmsm dtc drive system are of major concern in this thesis

    定子電阻變化，直流母線電壓漂移，開關器件反向相電壓降、逆變器死區時間引起的電壓誤差的補償，提高系統穩態運行性能以及永磁同步電機直接轉矩控制的無速度傳感器運行方案等問題都是本文研究的重點。轉矩的快速響應是直接轉矩控制演算法的一個卓越的性能。
  4. Firstly, a new joint filterbank precoders and decision feedback equalizers structure is proposed, and the corresponding optimization result based on the maximal mutual information criterion is derived. secondly, the concept of dt canonical model is proposed, which is very suitable for the task of blind signal processing based on the second - order statistical of the observations. thirdly, the methods of blind equalization and identification of the tv dispersive channels are researched systematically based on the proposed dt canonical model, and a subspace blind identification algorithm of the time - invariant channel matrix is developed

    本文創新性的成果在於：提出了預編碼-判決反饋聯合均衡系統結構，並從理論推導得出了對應的最大互信息量最優化設計結果；首次提出了時變色散通道的離散正則模型概念，該模型適宜於利用觀察數據的二階統計量進行盲信號處理；基於離散正則模型對時變色散通道進行了系統的盲均衡和盲辨識方法研究，提出了對時不變通道矩陣的子空間盲辨識演算法；針對誤差傳播效應問題，提出了可以消除誤差傳播效應的兩級盲辨識演算法；提出了基於離散正則模型的直接盲均衡演算法；提出了基於特徵恢復思想的神經網路直接自適應盲均衡演算法。
  5. First, in this paper, powercontrol technology is discussed, including its principle, methods of realization and status of research. then reverse outer - loop power controlarithmetic based on fer ( frame error rate ) measurement and adaptive variablestep - size inner - loop power control arithmetic are proposed. the simulation is doneand the result shows the deviation is smaller using the arithmetic fortracking the idealfer

    然後在此基礎上給出了基於誤幀率fer （ frameerrorrate ）測量的反向外環功率控制優化演算法和自適應變步長內環功率控制演算法，計算結果表明，與傳統的外環演算法相比本文模型化的演算法對目標fer的跟蹤具有較小的誤差。
  6. In order to satisfy the requirement of the given precision, the connection power of the networks is studied and adjusted using the baekpropagation training algorithm ( bp algorithm )

    採用誤差反向傳播演算法（ bp演算法）對網路的連接權值進行學習和調整，以滿足給定的精度要求。
  7. Design of on - line learning based error back propagation algorithm in simulation servo system

    基於在線學習誤差反傳演算法的模擬伺服系統設計
  8. Chapter 4 presents an error back propagation algorithm with quadratic momentum of the multilayer forward neural networks that will speed up the error convergence velocity

    本文提出一種帶二次動量項的多層前向網路誤差反傳演算法，提高了神經網路的誤差收斂速度。
  9. Feature extraction through 2 - order polynomial fit of the descending part of the response curve made possible a timesaving measurement process. the performances of two pattern recognition algorithms, namely principal component analysis ( pca ) and linear discriminant analysis ( lda ) in practical problems were discussed. artificial neural network ( ann ) was utilized with back - propagation algorithm ( bpa ), and the combination of pca / lda with ann improved the identification performance of the system

    基於對模式識別系統的深入研究，提出了從響應階段數據提取特徵的方法，節省了測試所需時間；比較了主成分分析法（ principalcomponentanalysis ， pca ）與線性判別式法（ lineardiscriminantanalysis ， lda ）兩種模式識別方法在實際應用中的不同結果，分析了原因；設計了採用誤差反傳演算法back - propagationalgorithm ， bpa ）的前向人工神經網路（ artificialneuralnetwork ， ann ） ，並指出其應用中存在的問題，提出了改進建議；利用pca lda與ann相結合的方法改善了系統的識別性能。
  10. 5 based on studying artificial nerve network theory, establish the nerve network model of cutting parameter. use back propagation algorithm ( bp algorithm ) as system ' s nerve network learning method. system has realized cutting parameter nerve network intelligentized choosing function

    5在深入研究人工神經網路理論的基礎上，建立了切削參數選擇的神經網路模型，採用誤差反傳演算法（即演算法）作為切削參數智能選擇的神經網路學習方法，實現了切削參數人工神經網路智能選擇功能。
  11. The simulation results indicate the capability of genetic algorithm in fast and steady learning of neural networks, guaranteeing a global convergence and overcoming some shortcomings of traditional error back propagation algorithms, meanwhile prove that this neural networks adaptive control structure is effective to many control problems and it is easy for us to programme and employ the method in the practical system

    模擬結果表明遺傳演算法能夠快速穩定地學習神經網路，保證全局收斂西安理工大學碩士學位論文並且能夠克服傳統誤差反傳演算法的一些缺點，也證明了這種神經網路自適應控制結構可以有效解決系統中存在的控制難題，同時編程容易，便於在實際系統中應用。
  12. The application of hybrid algorithm which combines improved genetic algorithm and error back - propagation algorithm in artificial neural network training is studied first

    首先研究了將改進遺傳演算法和誤差反向傳播（ bp ）演算法相結合的混合演算法來訓練人工神經網路。
  13. In this article we use a bp neural network to classify the eddy current signal and its result is also presented, which indicate that artificial neural network has vast potential in eddy current signal processing

    本文選用基於誤差反向傳播（ bp ）演算法的神經網路對信號分類，並給出分類結果，表明了神經網路在渦流材質檢測信號處理中應用的巨大潛力。
  14. Secondly, binary probability hypothesis detection is studied and is utilized as actuators " fdi residual decision. thirdly, multi - layer feed - forward ann and error backward propagation ( bp ) algorithm are studied and are utilized as control surfaces " failure detection and sortation

    第三，研究多層前饋神經網路及相應的bp （ errorbackwardpropagation誤差反向傳播）演算法，設計基於模型殘差的故障分類器，並通過其來完成全局舵面的故障檢測與分類。
  15. The living example certification indicates that the neural networks model of this paper possesses the good convergence with the error back - propagation algorithm, and can pledge the satisfactory mapping precision, and gain the forecasting result of ideal, and provides the reliable basis for the policy decision

    實例驗證表明本文的神經網路模型用誤差反向傳播演算法具有良好的收斂性，能夠保證滿意的映射精度，取得了理想的預測結果，為決策提供了可靠的依據。
  16. 2. based on the original bp network, some improvement on error back propagation arithmetic is made. the executing speed of the algorithm is increased through online adjustment of learning rate. combined with traditional pid control, this method generated two integral schemes : bp network + pid serial control and self - confirming control of parameters of pid controller based on bp network are constructed

    在原有的誤差反向傳播（ bp ）網路的基礎上，對其學習演算法進行了改進，通過在線調節學習速率，提高了演算法的實現速度，並且與傳統的比例積分微分（ pid ）控制方法進行結合，分別實現了兩種集成方法： bp網路與pid串列控制方法和基於bp網路的pid參數自整定控制方法。
  17. The bic method generalized from ar model was adopted to determine the number of input neurons in grnn prediction model. the grnn was applied to single - step and multi - step ahead prediction of the vibration time series of a rotating machine, and its performance was compared with that of 3 - layers perceptrons network with error back propagation training algorithm ( bpnn ). it is indicated that the grnn is more appropriate for prediction of time series than the bpnn, and the performance of grnn is qualified even with sparse sample data

    研究了基於廣義回歸神經網路（ grnn ）的大型旋轉機械振動狀態預測，提出了應用bic準則確定grnn預測模型輸入神經元數目的方法，將grnn用於大型機組振動峰?峰值時間序列的預測，與採用誤差反向傳播學習演算法的三層前饋感知器網路（ bpnn ）的預測結果對比表明， grnn的預測性能優于bpnn ，而且，即使樣本數據稀少，也能獲得滿意的預測結果。
  18. Applying this classic pattern recognition theory and artificial networks method, this paper proposes the analog fault diagnosis principles with backward - propagation neural network ( bpnn ) algorithm implementation

    本文有針對性的提出了模擬電路故障診斷前向多層誤差反傳（ bp ）網路的演算法實現途徑。
  19. Firstly, on the basic of normal error back propagation algorithm ( bp a1gorithm ), the model was added the inertia impulse item in the updating formula for weight, and then let learning rate and inertia parameter adjust ll self - adaptively, so the improved bp algorithm ( improved bp algorithm, ibp algorithm ) formed

    首先，該模型在誤差反向傳播演算法（ bp演算法）的基礎上，在網路權值更新公式中添加慣性沖量項，並對學習率和慣量因子進行自適應調整，從而形成bp改進演算法（ improvedbp演算法，簡稱ibp演算法） 。
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