梯度演算法 的英文怎麼說

中文拼音 [tīdùyǎnsuànfǎ]
梯度演算法 英文
hill climbing algorithm
  • 梯 : Ⅰ名詞1 （梯子; 樓梯） ladder; stairs; steps; staircase 2 （姓氏） a surname Ⅱ形容詞（形狀像樓梯的...
  • 度 : 度動詞[書面語] （推測; 估計） surmise; estimate
  • 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...
  1. The hybrid algorithm raises the convergence rate of the conjugate gradient method and solves the problem for which the convergence rate of the steepest descent method get slower when the isopleth of goal function is oblong

    這種混合優化演算法結合了共扼梯度法和最速下降法產生搜索方向，既提高了共扼梯度演算法的收斂速度，又解決了目標函數的等值線是扁長橢球時，最速下降法下降緩慢的問題，具有收斂速度快、收斂范圍大、適應面廣等特點。
  2. A derivative - free algorithm for unconstrained optimization

    求解無約束優化問題的免梯度演算法
  3. The cg algorithm does not require construction of the global matrix. it can be implemented efficiently on a abstract massively parallel architecture

    共軛梯度演算法不需要構造全局矩陣，它在大規模并行結構中能被有效地實現。
  4. In the algorithm level, currently various training algorithms of neural networks, including gradient algorithms, intelligent learning algorithms and hybrid algorithms, are comparatively studied ; the optimization principle of bp algorithm for neural networks training is analyzed in detail, and the reasons for serious disadvantages of bp algorithms are found out, moreover, the optimization principle of two kinds of improved bp algorithms is described in a uniform theoretic framework ; and the global optimization algorithms of neural networks, mainly genetic algorithm are expounded in detail, it follows that a improved genetic algorithm is proposed ; finally the training performances of various algorithms are compared based on a simulation experiment on a benchmark problem of neural network learning, furthermore, a viewpoint that genetic algorithm is subject to " curse of dimension " is proposed

    在演算法層，本文對目前用於神經網路訓練的各種演算法，包括梯度演算法、智能學習演算法和混合學習演算法進行了比較研究；對用於神經網路訓練的bp演算法的優化原理進行了詳細的理論分析，找到了bp演算法存在嚴重缺陷的原因，並對其兩類改進演算法-啟發式演算法和二次梯度演算法的優化原理，在統一的框架之下進行了詳盡的理論描述；對神經網路全局優化演算法主要是遺傳演算法進行了詳細的闡述，並在此基礎上，設計了一種性能改進的遺傳演算法；最後基於神經網路學習的benchmark問題對各種演算法在網路訓練中的應用性能進行了模擬研究，並提出了遺傳演算法受困於「維數災難」的觀點。
  5. Also, the author ’ s design strategy and creativity has been given in this paper. specifically, it includes : based on the feasibility analysis of the fit selection of control parameters in the aeration process, the aeration process of wastewater treatment of the joint - constructional complete - mixed activated sludge process has been aimed at in this paper. then, the state equations of the aeration process have been proposed in this paper, which is on the base of dissolved oxygen concentration ( do ) and discharge quantity of sludge ( qw ) as control variables, the concentration of bod and sludge as state variables. based on the present study on optimization control of wastewater treatment, the multivariable optimal control model with restriction factor has been presented in the paper with introducing modern control theory and system analysis into the field of activated sludge wastewater treatment,

    具體包括:以完全混合、表面曝氣合建式活性污泥工藝的污水處理曝氣過程為研究對象，在闡述了曝氣過程式控制制參數選取可行性的基礎上，建立了以溶解氧濃度do和活性污泥排放量qw為控制變量，以曝氣池中有機物濃度s和微生物濃度x為狀態變量的活性污泥曝氣過程的基本狀態方程;運用現代控制理論的觀點和污水處理理論，在現有關于污水處理最優控制問題研究的基礎上，建立了有約束條件多變量能耗最小數學模型，該數學模型是以有機物排放總量和狀態變量的末值條件作為約束條件，曝氣過程的能耗最小作為目標泛函;採用增廣拉格朗日乘子法對最優控制問題進行轉化，並對應用極大值原理求解能耗最小這一最優控制問題進行了詳細的解析;引入約束運算元，應用具有控制約束的共軛梯度演算法對能耗最小這一最優控制問題進行求解，並進行模擬實驗驗證。
  6. In this control structure, an svm is used as identifier, the control signal is solved by an exponentiated gradient algorithm

    該控制結構以支持向量機為辨識器，並用指數梯度演算法來求控製作用。
  7. Here the changes lie in constantly trying out new wirings of the enigma plugboard

    梯度演算法逐步對對象（在此情況下為線路連接板設置）進行改變，以此來優化對象。
  8. It has been deduced that the search direction remains the same but that the step length decreases in optimizing the improved cost function with the conjugate gradient algorithm from the gradient of the cost function that the fir filter apporaches the contrary point spread function ( psf ) more, and that the estimated image is closer to the original one

    從代價函數的梯度入手推導出共軛梯度演算法，其搜索方向保持不變而搜索步長變小，使濾波系數更加退近於點擴展函數逆運算元，從而使估計圖像與原始圖像更加接近。
  9. Reinforcement learning algorithms that use cerebellar model articulation controller ( cmac ) are studied to estimate the optimal value function of markov decision processes ( mdps ) with continuous states and discrete actions. the state discretization for mdps using sarsa - learning algorithms based on cmac networks and direct gradient rules is analyzed. two new coding methods for cmac neural networks are proposed so that the learning efficiency of cmac - based direct gradient learning algorithms can be improved

    在求解離散行為空間markov決策過程（ mdp ）最優策略的增強學習演算法研究方面，研究了小腦模型關節控制器（ cmac ）在mdp行為值函數逼近中的應用，分析了基於cmac的直接梯度演算法對mdp狀態空間離散化的特點，研究了兩種改進的cmac編碼結構，即：非鄰接重疊編碼和變尺度編碼，以提高直接梯度學習演算法的收斂速度和泛化性能。
  10. This paper discuss a modeling and predicting means for nonlinear systems proceeding from nonlinear systems modeling and predicting theory, whch is based on drnn model. this means overcomes the fact that ar model is used only in linear systems, at the same time it connects itself with approximation theory symbolic statistics and conjugate gradient algorithm, and formulate a system of large watercrafts motion modeling and predicting which is based on drnn model, and simulate it

    本論文從非線性系統建模與預報的理論及應用觀點出發，系統地闡述了一類適用於非線性系統的建模預報方法? ?基於drnn模型的建模預報方法，克服了ar模型僅局限於線性的情況，同時結合逼近論、數理統計等知識，運用共軛梯度演算法，提出並建立了基於對角回歸神經網路的大型艦船運動建模預報系統，並進行了模擬。
  11. Firstly the stochastic gradient algorithm based on minimum mutual information ( mmi ) is researched, and this algorithm is simple and stable, but its convergence speed is slow. secondly the natural gradient algorithm based on riemann space is researched. finally easi algorithm, iterative inversion algorithm and some

    首先研究了基於最小化互信息的隨機梯度演算法，該演算法簡單穩定但收斂較慢，然後研究了基於黎曼空間的自然梯度演算法，最後介紹了easi演算法、迭代求逆演算法以及其餘一些演算法。
  12. The convergence theorem of a class of conjugate gradient algorithms is proven, which extend the main convergence theorem in gilbert and noceda ( 1992 )

    討論了一類共軛梯度演算法的收斂性，推廣了1992年gilbert和nocedal的收斂性結果。
  13. Based on the papers [ 10 ] and [ 19 ], we propose a new nonmonotone conjugate gradient algorithm, prove its convergence and test the new nonmonotone algorihm

    基於文獻[ 10 ]和[ 19 ] ，我們提出了一種新的非單調共軛梯度演算法，證明了新演算法的收斂性，並對它進行了測試。
  14. This paper is devoted to some numerical optimization methods and optimization models for solving practical problems in real world. the methods we concern with are the conjugate gradient algorithms, evolutionary algorithms and goal programming

    本文對近年來備受關注的幾類最優化方法（共軛梯度演算法、進化演算法和目標規劃法）的理論性質及應用進行了研究，主要研究成果如下： 1
  15. At one time the thesis look back the part parallel interference cancellation detection, and update the algorithm of the multiuser with lms algorithm. at last, the thesis presentes the blind multiuser detection with adaptive algorithm the blind multiuser detection base on kalman algorithm and probabilistic algorithms for blind adaptive multiuser detection

    同時對部分并行干擾多用戶檢測器進行了回顧，並用lms演算法實現了多用戶檢測器的演算法更新。最後對盲多用戶檢測的自適應演算法進行了介紹，構造基於kalman濾波的盲多用戶檢測器，並對隨機梯度演算法進行了誤碼性能的分析。
  16. Global convergence results of a new three terms conjugate gradient method with generalized armijo step size rule

    步長搜索的一類新的三項共軛梯度演算法及其收斂特徵
  17. After discussing this kind of filter in this paper in detail, the grads algorithm in time domain and frequency domain is set up when the change of frequency is slow, so it means the algorithm only process the narrowband interference what it changes slowly

    論文對數字自適應外差濾波器進行了詳細的研究，建立了自適應外差濾波器的時域和頻域的梯度演算法，該演算法的推導使用了外差頻率變化緩慢的假設，這意味著該濾波器只能夠處理慢變的窄帶干擾。
  18. The least square conjugate gradient and odd values decomposition method also can be used to perform tomographic inversion

    研製的最小平方共軛梯度演算法和奇異值分解法也可進行同樣的層析反演。
  19. The cost function of the optimal control problem is a weighted sum of the squared horizontal and vertical components of the helicopter velocity at touchdown. the control ( horizontal and vertical components of the thrust coefficient ) required to minimize the cost function is obtained using nonlinear optimal control theory

    其次，定義最優控制問題的性能指標為直升機著陸時的水平和垂直速度的加權平方和為最小，並採用一階梯度演算法得到使性能指標最小的控制規律。
  20. Hill climbing algorithms try to optimize an object, in this case the plugboard settings, by changing the object step by step

    梯度演算法逐步對對象（在此情況下為線路連接板設置）進行改變，以此來優化對象。
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