線路收斂 的英文怎麼說

中文拼音 [xiànlùshōuliǎn]
線路收斂 英文
path convergence
  • 線 : 名詞1 （用絲、棉、金屬等製成的細長的東西） thread; string; wire 2 [數學] （一個點任意移動所構成的...
  • 路 : 1 （道路） road; way; path 2 （路程） journey; distance 3 （途徑; 門路） way; means 4 （條理） se...
  • 收 : Ⅰ動詞1 （把攤開的或分散的事物聚集、合攏） put away; take in 2 （收取） collect 3 （收割） harvest...
  • 斂 : Ⅰ動詞1 （收起; 收住） hold back; keep back 2 （約束） restrain 3 （收集; 徵收） gather; collect; ...
  • 線路 : 1. [電學] circuit; line 2. [交通運輸] line; route
  • 收斂 : 1 （減弱或消失） weaken or disappear 2 （約束言行） restrain oneself 3 [數學] convergence; constr...
  1. This paper has proposed a method controlling iteration number and stability of solution according to thought of integral convergence algorithm minimizing nonlinear equations

    本文利用求非線性方程組極小化全局收斂法的思路，提出了控制迭代收斂次數、控制反演解穩定的方法。
  2. 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
  3. Considering the one - sidedness and inaccuracy of knowledge discovery only from single - color database, an approach is proposed to discover knowledge from 1331 groups of mix - color database with partial least - square regression, based on measuring and learning 400 groups of single - color database. by this method, the mean error decreases when converting from rgb to cmyk, the precision of color matching is improved, and the automatic and general problem in color matching is further solved

    本文基於統計學習理論構造了一種快速自適應隨機搜索演算法，證明了演算法的收斂性.給出了一種簡易實用的寬帶天線匹配設計新方法.應用該自適應演算法進行天線匹配設計，不僅演算法簡單，易於編程實現;而且能夠快速設計出具有較好性能的匹配網路，非常適用於各種短波、超短波天線的匹配設計問題
  4. Application of the algorithm for different observed head data sets indicate that the model can be successfully applied for aquifer systems where data available may be sparse and with errors. calculated groundwater heads by identification results in fourteen parameter areas are fit for observed heads in field, and flowing filed is similar. the study demonstrates the effectiveness of the ga global optimization model for parameter identification, which is an important step towards real system simulation and effective planning and management of groundwater resources

    通過算例研究，表明上述演算法可行，且rbf神經網路方法和退火遺傳演算法對地下水系統參數的識別效果都較好，而退火遺傳演算法較之標準的遺傳演算法具有更好的收斂性將演算法應用到北京市密懷順地區，在收集、分析研究區資料基礎上，建立了北京市密懷順平原區地下水模擬模型，並用遺傳演算法進行了地下水系統參數識別，在十四個分區情況下，計算水位與實際水位擬合的較好，各應力期末的計算與實測等水位線基本一致，表明該識別值較為合理。
  5. Finally, take example for a non - linear function, method mentioned in this paper is used to design wavelet neural network to approximate this function. the computer simulations confirm the method that is brought out in this paper is useful, and prove that wavelet neural network has not only fast convergence and better precision of approximation, but also good capability of forecasting and escaping error

    最後，對於一個實際的非線性函數，用本文介紹的方法來設計小波神經網路來逼近函數，模擬結果表明該方法的有效性，並且表明小波神經網路在函數逼近上，網路的收斂速度快，逼近精度高的特點，並且網路具有很好的泛化能力和容錯性。
  6. The new algorithm starts from an initial estimate which is based on the hough transform, and a rectangular window is centered using the current line approximation, and a new line estimation is generated by making a total least squares fit through the pixels contained within the window. this is repeated until convergence is reached. lastly, we have suggested a new technique which may recover the motion and structure parameters of a moving object by using of 21 optical flow lines based on the optical flow fields of the feature line this thesis is the project supported by aeronautical foundation science ( no. 99f53065 ) and research center of measuring and testing technologies, and control engineering in nanchang institute of aeronautical technology ( no. 2001 - 15 )

    演算法的思路是：首先，在小區域內運用霍夫變換確定直線的初始值；其次，以直線的初始值所對應的直線為中心線，建立一個矩形框；最後，利用矩形框內所包含的邊緣點數據不斷地迭代直至收斂，從而達到進一步修正直線的坐標參數；本文基於特徵直線的光流場，即線流場，建立了一種利用21條光流線確定空間三維物體旋轉運動參數、平移運動參數以及對應的空間直線坐標的線性演算法。
  7. Aim at the dtc ' s blemish mentioned above and the direction of dtc technique development, the dissertation put great emphasis on the work as follows, with an eye to exalt dtc system function : ( 1 ) a new speed - flux observer of an induction motor is proposed to enhance the accuracy of flux observing, which is an adaptive closed - loop flux observer and different from the traditions. a new adaptive speed - observation - way is deduced out according to the popov ' s stability theories ; ( 2 ) to improve the performance of dtc at low speed operation, we have to exalt the accuracy of the stator flux estimation and a new way of bp neural network based on extended pidbp algorithm is given to estimate and tune the stator resistance of an induction motor to increase the accuracy of the stator flux estimation ; ( 3 ) digital signal processor is adopted to realize digital control. an device of direct torque control system is designed for experiment using tms320lf2407 chip produced by ti company ; ( 4 ) bring up a distributed direct torque control system based on sercos bus, sercos stand for serial real time communication system agreement which is most in keeping with synchronous with moderate motor control ; ( 5 ) the basic design frame of the hardware and software of the whole control system is given here and some concrete problem in the experiments is described here in detail

    針對上面提到的直接轉矩控制的缺陷和未來直接轉矩控制技術發展方向，本論文重點做了以下幾個方面的工作，目的在於提高dtc系統的綜合性能： （ 1 ）提出一種新型的速度磁鏈觀測器，新型的速度磁鏈觀測器採用自適應閉環磁鏈觀測器代替傳統的積分器從而提高磁鏈觀測的精度，並且根據popov超穩定性理論推導出轉速的新型自適應收斂律； （ 2 ）改善系統的低速運行性能，主要從提高低速時對定子磁鏈的估計精度入手，提出了一種提高定子磁鏈觀測精度的新思路? ?利用基於bp網路增廣pidbp學習演算法來實時在線地修正定子電阻參數； （ 3 ）採用數字信號處理器dsp實現系統全數字化硬體控制，結合ti公司生產的tms320lf2407晶元，設計了直接轉矩控制系統的實驗裝置； （ 4 ）提出了基於sercos總線網路化分散式的直接轉矩控制系統， sercos （ serialrealtimecommunicationsystem ）是目前最適合同步和協調控制的串列實時通信協議； （ 5 ）基本勾勒出整個控制系統的硬體和軟體設計基本框架，詳細描述一些實驗中的具體的細節問題。
  8. To quicken convergence and improve model precision, a new algorithm is presented in this paper, which utilize construct orderliness property of self - organization feature maps ( sofm ), divide system input space and adopt 1 order or 2 order local model in each subspace individually instead of a global model

    為了提高收斂速度和模型精度，本文利用自組織映射網路拓撲有序特性，對系統輸入空間進行分割，在子空間中採用多個局部一階線性模型或二階模型代替全局模型的局部化方法。
  9. In the first chapter, we narrate the characteristic of convertible bond, give some clues about development and actuality of the market and its pricing theory ; in the second chapter, we introduce modeling idea and some material problems in the model in detail, draw the yield curve which is very important to the model by spline method ; in the third chapter, we first explain the basic idea and convergent speed of monte carlo method, then, give the mathematical description for financial market, prove equivalence of non - arbitrage market, existence of risk neutral probability measure in the market and the price process of underlying asset is a martingale ; in the forth section, we introduce how to simulate stock price path by monte carlo method in detail, based on foregoing result, we prove the path is a martingale, thereby, the model is logical

    本文第一章先對可轉債的特點、市場發展和現狀及其定價理論的發展和現狀作一概述;第二章詳細介紹了建模思想和模型中的一些具體問題，利用spline方法繪出了在模型中具有重要作用的收益曲線;第三章首先敘述了montecarlo方法的基本思想和有關其收斂速度的一些性質，然後從數學的角度給出了對金融市場的描述，證明了市場無套利、市場存在風險中性概率測度及標的資產價格過程為鞅的等價性;在第四節中，對用montecarlo方法模擬的帶跳股價路徑作了詳細介紹，並利用前兩節的結論證明了模擬的帶跳股價路徑為一個鞅過程，從而保證了模型在理論上的合理性。
  10. Normal bp algorithm can be used in many fields and resolved many practical problems, however, normal bp algorithm has many limitations such as it ' s easy to fall into the local minimum in the course of convergence, its " convergent speed is very slow, the method which set the structural parameter and the operational parameter has n ' t be widely accepted, and so on

    標準bp演算法應用甚廣，解決了許多的實際問題，但同時它也存在著諸如在收斂過程中容易陷入局部最小點、收斂速度很慢以及網路的結構參數（隱層數、隱層單元）和運算參數（步長、非線性函數的選擇）等都尚無公認的理論指導等問題。
  11. This paper describes a reconstructive algorithm which is based on network theory for electrical capacitance tomography technic. there are twelve electrodes in the system. the permittivity distribution of flow with two components within a pipeline is reconstructed. assume the permittivity distribution of the region to be reconstructed. then whole measured area is discretized into a network composed of capacitance. the measurement circuit which contains a pair of source electrode and detecting electrode is taken as a four - terminal network. the across admittance of the four - teminal network is proportional to the capacitance between the source electrode and the detecting electrode. modify the distribution of the permittivity according to the difference between the calculated capacitance and measured capacitance. the experimental results show that this algorithm is effective and can coverge

    本文描述了一種用於兩種成份的流體成像的12電極電容層析成像新方法.該方法基於電路的網路理論，首先對重建區域假定一個介電率分佈，用電容網路作為離散化模型，將每一個源電極和探測電極對組成的測量電路看作一個四端網路，該四端網路的跨導與源電極和探測電極之間的電容值是線性關系，這個電容值和測量得到的電容值之間存在誤差，根據這個誤差對修正介電率分佈.通過對不同介質分佈作的模擬實驗結果，證實了該演算法是有效的，收斂的
  12. This paper presents a model of cosine basis functions neural network based on bp algorithm, discusses the relation between the algorithm of neural network and amplitude - frequency characteristic about the linear phase fir filter, introduces the convergence condition of neural network algorithm, and studies the optimal design example about the high - order fir double - band - pass filters

    提出了一種基於bp演算法的正弦基函數神經網路模型及演算法的收斂條件，研究了該神經網路演算法與fir線性相位濾波器幅頻特性的關系，給出了高階雙通帶濾波器的優化設計實例。
  13. However, the neural network easily falls into local minimum, and weakly search the overall situation. the genetic algorithm ( ga ) has the ability of searching overall situation. the genetic neural network recombines the genetic algorithm ’ s of seeking the superior overall situation and the neural network ’ s nonlinear characteristic and rapid convergence

    但神經網路具有易陷入局部極小值以及全局搜索能力弱等缺點;而遺傳演算法具有較好的全局最優搜索能力，遺傳神經網路將兩者結合，既保留了遺傳演算法的全局尋優的特點，又兼有神經網路的非線性特性和收斂的快速性。
  14. First by introducing nonlinear measures, the existence, uniqueness and global exponential stability of the equilibrium point of this kind of neural networks are investigated. two different lipschitz continuous activations are considered. some sufficient conditions and convergence estimate for global exponential stability of neural networks are obtained on condition that self - feedback is nonlinear

    第一種是通過引入非線性測度的概念，分別對激勵函數採用了兩種不同的lipschitz連續假設，給出這兩種不同連續假設下神經網路系統的全局指數穩定性條件，並分析其指數收斂率。
  15. By giving some properties of the double dogleg path, we prove the global convergence and fast local convergence rate of the proposed algorithm under some reasonable conditions

    通過給出雙折線路徑的一些性質，在合理的條件下，我們證明了所提供演算法具有整體收斂性並得到局部收斂速率。
  16. For the time - invariant linear systems, we transform the problem of observer design to a special type of constrained nonlinear programming and present the method to solve this programming using hopfield network, then, prove the convergence of the network

    本文將線性時不變觀測器的設計問題轉化為一類特殊的約束非線性優化問題，給出了利用hopfield網路求解該問題的方法，證明了該方法的收斂性。
  17. Later on, after elaborating the disadvantages of the old methods in detecting and recognizing moving objects, a series of corresponding approaches are proposed, such as grid scan, local tracking bug and dynamic window in object tracing to reduce the huge data needed to be processed, maximum and minimum for selecting a proper segmentation threshold and improved conversion from rgb model to hsv and so on to decrease the influence of inhomogeneous lighting and the color noise, a bilinear interpolation in each quadrant to eliminate the bad effect on the recognition precise because of the distortions of the camera. after that, much emphasis is given on application study in pattern recognition with a feed - forward neural network. both the basic bp algorithm and improved bp algorithm in the study process are described in detail, and the later is used to quicken convergence speed and improve validity of the network

    然後，分析和闡明了傳統的運動目標檢測方法的不足，並在此基礎上結合研究中的實際實驗環境，提出了一系列解決方法，包括針對降低龐大數據量而提出的網格掃描、局部「跟蟲」追蹤和動態窗口掃描等目標檢測方法，針對實驗環境中光照不均和顏色干擾提出基於人機交互的最大最小值閾值選取方法和引入改進的rgb模型到hsv模型的轉換方法，為消除圖像畸變對識別精度的惡劣影響而採用的通過控制點進行雙線性插值進行畸變校正的方法；緊接著，概述了神經網路的發展歷史和幾種常用神經網路模型的特點，重點研究了前饋型神經網路在模式識別中的應用問題，詳細闡述了基本的bp演算法和學習過程中bp演算法的改進，從而使網路收斂速度更快，解決問題更有效，並在此基礎上，設計了一個基於bp神經網路的運動目標識別系統，給出了實驗結果。
  18. The several ones that have more lager sensitivity to embankment settlement are found out. then, aimed at the traditional three - layer bp network ' s shortages : easily getting into local minimum value and slow convergence, the modification combined momentum method with self - adaptation study velocity is made, and one improved bp network is put forward. finally, according to the results from above sensitivity analyses, the nonlinear model main parameters of each natural layer in roadbed are approximately rectified using the improved bp network technology founded on its stronger nonlinear mapping capacity and the settlement measurements

    採用非線性有限元程序，對鄧肯-張模型中8個參數與路堤沉降的關系進行了詳細分析，找到了影響沉降的主要參數；接著，針對傳統的三層bp網路具有收斂速度慢、易陷入局部極小點等不足，對其進行了修正，提出了改進的bp神經網路模型；最後，根據上述靈敏度分析結果，基於改進的bp網路模型較強的非線性映射能力和前期沉降實測資料，對路基中各天然土層的非線性模型主要參數進行了反分析修正； （ 4 ）路堤沉降計算一維法中考慮應力歷史、側向變形的研究。
  19. Radial basis function neural network ( rbfnn ) is chosen to build predictive model. rbfnn is a special type of neural network linear - in - weight in nature and having nonlinear processing properties. finally, an adaptive filter is applicable to do the followed weak signal extraction work

    接著選用徑向基函數神經網路（ radialbasisneuralnetwork ， rbfnn ）建立混沌時間序列預測模型，徑向基函數神經網路是一種局部逼近的人工神經網路，訓練簡潔而且學習收斂速度快，能夠逼近任意非線性函數，最後將預測誤差送入自適應信號分離器進行處理，檢測出微弱信號。
  20. The radar target identification based on artificial neural network is the protagonist of the chapter 4. bp network and wavelet network are used to classified the emulational radar targets. with the powerful capability of non - linnear identification of bp neural network, its ’ born limitations such as local extremum, slow convergence etc. can be reformed by the wavelet network, which is a network with a wavelet function embedded into the node of a bp network

    研究了基於人工神經網路模型的雷達目標hrrp識別方法。 bp人工神經網路強大的非線性處理能力，在解決復雜目標分類識別時有優勢;小波神經網路針對bp網路的不足，將bp網路和小波變換相結合，在網路收斂、網路初始化方面彌補了bp網路的部分缺陷，其識別性能和抗噪性能與bp網路相比有所提高。
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