convergence of algorithm 中文意思是什麼

convergence of algorithm 解釋
演算法的收斂
  • convergence : n. 1. 聚合，會聚，輻輳，匯合。2. 集合點；【數、物】收斂；【生物學】趨同（現象）。
  • of : OF ＝Old French 古法語。
  • algorithm : n. 【數學】演算法；規則系統；演段。
  1. Studies on correct convergence of the em algorithm for gaussian mixtures

    演算法正確收斂性的探討
  2. First, we consider an additive schwarz algorithm for the solution of ax 4 - f ( x ) 0, x when coefficient a is an m - matrix and f ' ( x ) 0. by applying the theory of weak regular splitting of matrices to the above considered algorithm, we obtain the weighted max - norrn bound for iterations. moreover, under the assumption that f ( x ) is concave, we establish monotone convergence of the considered algorithm

    本文內容如下：首先，應用加性schwarz演算法求解非線性互補問題，其中a是m陣，應用弱分解理論，我們獲得了在加權范數意義下誤差的幾何收斂速度，在f （ x ）是凹函數的假設下我們還獲得了此演算法的單調收斂性，同時我們給出此演算法的一種修改演算法，無需前面的假設，該演算法具有單調收斂性。
  3. A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand. deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time, the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm. moreover, by introducing memory function and vaccine inoculation mechanism of immune system, at the same time, deca can converge to the optimal solution rapidly and stably. the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models. the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples, and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes

    針對模糊聚類演算法不適應復雜環境的問題，提出了一種新的動態進化聚類演算法，克服了傳統模糊聚類建模演算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度，實現對聚類個數進行全局尋優;利用fcm演算法加快聚類中心參數的收斂;並引入免疫系統的記憶功能和疫苗接種機理，使演算法能快速穩定地收斂到最優解.利用這種高效的動態聚類演算法辨識模糊模型，可同時得到合適的模糊規則數和準確的前提參數，將其應用於控制過程可獲得高精度的非線性模糊模型
  4. In this paper, we present a theoretical analysis on the correct convergence of the em algorithm for gaussian mixtures

    本文對高斯混合體em演算法的正確收斂性問題進行了理論研究。
  5. In the second part, a decomposition method for solving semidefmite quadratic programming with box constraints is proposed. a regular splitting of the hessian matrix of the problem is used in the algorithm. the convergence of the algorithm is proved under certain assumptions, the numerical results are also given

    第二部分把解邊界約束正定二次規劃問題的正則分解演算法推廣到求解邊界約束半正定二次規劃問題，在理論證明的基礎上還進行數值檢驗，結果說明演算法是有效的。
  6. Abstract : in this paper a new identification model constructed by neural networks with modified inputs and stable filters is presented for continuous time nonlinear systems in order to reduce the inherent network approximation errors. an adaptive law with projection algorithm is employed to adjust the parameters of networks. under certain conditions, convergence of the identification error is proved

    文摘:在用神經網路進行系統建模時，建模誤差的存在是難免的.為了減小這種誤差，本文對連續時間非線性系統提出了一種新的神經網路辨識模型，它是由帶有輸入修正的神經網路和穩定濾波器組合而成.文中給出了權值的學習演算法，即權值是根據辨識誤差的投影演算法來改變，證明了在一定條件下辨識誤差的收斂性
  7. As a result, controllers cannot output signals according to the computation result of algorithm, original iterative rules are affected, and it even affects the convergence of the algorithm. in this paper, discussion of this problem was presented

    這樣控制器就無法按照迭代學習演算法的計算結果正常輸出，迭代學習控制律原有的迭代關系被破壞，並有可能破壞迭代學習控制演算法的收斂性。
  8. Finally, jinduicheng mo. company open - pit is quoted as an instance for building mine transportation vechile scheduling system model, and according to the model, adopt genetic algorithm to study the optimization of mine transportation vechile scheduling system. a rational project is given to this problem, the paper also analysized the optimial design of mine transortation vechile scheduling, the model offering in this paper, convergence of optimal algorithm and data bank management, and transportation project of minerals and disposals is optimized, which realize the decision of transportation project and data visibilization, and wich improves the science and information process of transportation department management

    最後，論文以金堆城鉬業公司露天礦為例建立礦山運輸車輛優化調度模型，結合所建立的礦山車輛優化調度模型，採用遺傳演算法對礦山運輸車輛系統進行優化研究，為其提供合理的體系方案。並對礦山車輛優化調度系統設計進行了詳細分析，提出的礦山車輛優化調度系統，集優化演算法與數據庫管理分析於一體，進行礦巖運輸方案的優化，實現調度方案決策的可視化、運行數據的可視化，促進運輸部門管理的科學化、信息化進程。
  9. At first, in order to prevent the premature convergence of genetic algorithm effectively, the author brings forward a novel dyadic floating - point supplementary mutation operator. then, simulating the natural evolution, the author presents a novel topology, unoriented - connected topology, for parallel genetic algorithm. in the end, an interval decomposed optimization method is brought forward for ipga, which can improve the optimization performance of the algorithm

    為提高演算法的性能，作者對遺傳演算法進行三種改進：首先，為克服遺傳演算法早熟收斂，作者提出一種新的二元浮點補碼變異運算元；其次，模擬生物自然進化模式，為并行遺傳演算法提出了一個新的并行拓撲結構- - - -無定向拓撲連接；最後，作者提出一種區間分解優化思想，來提高對最優解的搜索能力。
  10. To make further study on the optimization capability of iga and other correlative capabilities mathematically, stochastic theory is used to analyze iga. as a result, the global convergence of iga and other correlative characteristics are got. meanwhile, the convergent effect and the mechanism on prevention from premature of iga is studied so that the effectiveness and the superiority of the algorithm proposed in the dissertation are proved theoretically

    為了從數學角度更加深入地分析iga的優化能力及相關性能，利用隨機過程理論對iga進行分析，並證明了iga的全局收斂性及其他相關性質，還對iga的收斂效果以及對早熟的防治機理進行了研究，從而在理論上證明了本文演算法的有效性和優越性。
  11. To combine it with the virtue of valuable earthquake damage experience accumulated in china and stored in damage matrix, an inversion strategy is designed to search seven ratios of 4 spectral displacements of buildings to the median values of spectral displacements of 4 damage states by the criteria of the convergence of the values of the standard deviations of the natural logarithm of the spectral displacements of four damage states as the objective function, a hybrid procedure integrated the simplex with the generic algorithm is adopted and the program is updated for this purpose from an existing one

    為了說明本文方法的實用性，以xx市xxx區的多層砌體房屋為例，根據地震危險性、建築物易損性、建築物和室內財產損失率、人口死亡率，分別計算出房屋、室內財產的期望損失率和損失率的方差、人口的期望死亡率和死亡率的方差，得到純費率，設附加費率為純費率的一定比例，求得毛費率。
  12. An algorithm for detecting moving ir point target in complex background is proposed, which is based on the reverse phase feature of neighborhood ( rpfn ) of target in difference between neighbor frame images that two positions of the target in the difference image are near and the gray values of them are close to in absolute value but with inverse sign. firstly, pairs of points with rpfn are detected in the difference image between neighbor frame images, with which a virtual vector graph is made, and then the moving point target can be detected by the vectors ' sequence cumulated in vector graphs. in addition, a theorem for the convergence of detection of target contrail by this algorithm is given and proved so as to afford a solid guarantee for practical applications of the algorithm proposed in this paper. finally, some simulation results with 1000 frames from 10 typical images in complex background show that moving point targets with snr not lower than 1. 5 can be detected effectively

    基於運動點目標在鄰幀差分圖像中所具有的近鄰反相特徵，即運動點目標的兩個位置相鄰近、灰度值一正一負，提出一種在復雜背景下，基於紅外序列圖像的運動點目標檢測演算法.本演算法利用該特徵在鄰幀差分圖像中檢測反相點對，進而構造反相點對矢量圖，最後依據累積反相點對矢量圖中多矢量首位相接的連續性檢測出運動的點目標.文中給出並證明應用本演算法能以概率1檢測到運動點目標的收斂性定理.對典型復雜背景下10幅1000幀圖像的模擬結果表明，當信噪比大於或等於1 . 5時，可以有效檢測出運動點目標
  13. A new recurrent neural network structure, self - feedback diagonal recurrent neural networks ( sdrnn ), is also designed in this chapter. the learning algorithm of sdrnn is given and the convergence of this algorithm is proved. the simulation results show the validation of the structure and the learning algorithm

    在局部遞歸神經網路結構方面，提出了一種遞歸神經網路結構? ?自環對角遞歸神經網路結構（ sdrnn ） ，給出了相應的學習演算法，證明了演算法的收斂性，並進行了模擬實驗。
  14. The characteristics of quantum computing and the mechanism of immune evolution are analyzed and discussed. inspired by the mechanism in which immune cell can gradually accomplish affinity maturation during the self - evolution process, a immune evolutionary algorithm based on quantum computing ( mqea ) is proposed. the algorithm can find out optimal solution by the mechanism in which antibody can be clone selected, memory cells can be produced, similar antibodies can be suppressed and immune cell can be expressed as quantum bit ( q - bit ). it not only can maintain quite nicely the population diversity than the classical evolutionary algorithm, but also can help to accelerate the convergence speed and converge to the global optimal solution rapidly. the convergence of the mqea is proved and its superiority is shown by some simulation experiments in this paper

    分析和探討了量子計算的特點及免疫進化機制，並結合免疫系統的動力學模型和免疫細胞在自我進化中的親和度成熟機理，提出了一種基於量子計算的免疫進化演算法.該演算法使用量子比特表達染色體，通過免疫克隆、記憶細胞產生和抗體相似性抑制等進化機制可最終找出最優解，它比傳統的量子進化演算法具有更好的種群多樣性、更快的收斂速度和全局尋優能力.在此不僅從理論上證明了該演算法的收斂，而且通過模擬實驗表明了該演算法的優越性
  15. Abstract : the characteristics of quantum computing and the mechanism of immune evolution are analyzed and discussed. inspired by the mechanism in which immune cell can gradually accomplish affinity maturation during the self - evolution process, a immune evolutionary algorithm based on quantum computing ( mqea ) is proposed. the algorithm can find out optimal solution by the mechanism in which antibody can be clone selected, memory cells can be produced, similar antibodies can be suppressed and immune cell can be expressed as quantum bit ( q - bit ). it not only can maintain quite nicely the population diversity than the classical evolutionary algorithm, but also can help to accelerate the convergence speed and converge to the global optimal solution rapidly. the convergence of the mqea is proved and its superiority is shown by some simulation experiments in this paper

    文摘:分析和探討了量子計算的特點及免疫進化機制，並結合免疫系統的動力學模型和免疫細胞在自我進化中的親和度成熟機理，提出了一種基於量子計算的免疫進化演算法.該演算法使用量子比特表達染色體，通過免疫克隆、記憶細胞產生和抗體相似性抑制等進化機制可最終找出最優解，它比傳統的量子進化演算法具有更好的種群多樣性、更快的收斂速度和全局尋優能力.在此不僅從理論上證明了該演算法的收斂，而且通過模擬實驗表明了該演算法的優越性
  16. Bounded convergence of forgetting factor least square algorithm for time - varying systems

    本系統是按照目前國際上高溫超導薄膜的微波表面電阻的測量標準方案
  17. 3 a novel recursive least - square ( rls ) blind space - time receiver algorithm based on the constrained condition, which can completely avoid the matrix inversion introduced into by constraints ( comparing with the normal rls ), is proposed for multi - path slow fading cdma channels. the computational complexity of this method is not only lower than that of the normal rls, but also lower than that of both lms and ls blind space - time receiver methods that are realized based on the rosen ' s gradient projection. and the speed of convergence of the presented rls blind space - time receiver algorithm is better than that of both lms and ls blind space - time receiver methods

    3 、針對多徑慢衰落通道下ds - cdma盲空時接收機中線性約束二次規劃問題提出一種新的遞歸最小二乘演算法，該演算法完全避免因約束而引進的矩陣求逆運算（相對于常規的遞歸最小二乘演算法） ，不但運算量比常規的要低，而且比基於rosen梯度投影實現的最小均方（ lms ）與最小二乘盲空時接收機演算法還低，且收斂速度比基於rosen梯度投影實現的最小均方（ lms ）與最小二乘盲空時多用戶檢測都好，將提出的新的遞歸最小二乘演算法與提出的數據選擇方案結合起來可以進一步降低其運算量，具有很大的實用價值，最後通過模擬實驗進一步分析了其性能。
  18. Combined with the traditional delaunay method, a new advancing front method was presented, which could ensure the convergence of algorithm. 3. a technique that can generate the initial coarser meshes was proposed

    將傳統的delaunay演算法和前沿生成演算法相結合，給出了一種新的前沿生成演算法，從而保證了前沿生成演算法的收斂性； 3
  19. Abstract : an algorithm of indefinite quadratic programming over unbound domain is presented ; the indefi nite quadratic programming is translated into a series of convex programming and the convergence of algorithm is discussed

    文摘:給出了無界域上不定二次規劃的一個演算法，該演算法將不定二次規劃轉化為一系列凸二次規劃，並證明了演算法的收斂性
  20. In second chapter, we chiefly express simply rationale of general genetic algorithm and simply algorithm foundation, then in fourth chapter, introducing the rationale of the distributed fusion genetic algorithm and model structure. because this paper is only a introducing assumption and simply application, it is not to prove the convergence of algorithm, and we must have work to do continuously

    在第二章，我們簡單描述了一般遺傳演算法的基本原理和簡單的演算法構造，然後在第四章提出了分散式融合遺傳演算法的原理和構造形式，當然由於本文只是一個初步的設想和簡單的實施，所以對于演算法的收斂性證明還不能得到，還有待進一步的解決和完善。
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