穩定反饋網路 的英文怎麼說

中文拼音 [wěndìngfǎnkuìwǎnglù]
穩定反饋網路 英文
stabilizing feedback network
  • 穩 : 形容詞1 （穩定; 穩當） steady; stable; firm 2 （穩重） steady; staid; sedate 3 （穩妥） sure; rel...
  • 定 : Ⅰ形容詞1 （平靜; 穩定） calm; stable 2 （已經確定的; 不改變的） fixed; settled; established Ⅱ動詞...
  • 反 : Ⅰ名詞1 （方向相背） reverse side 2 （造反） rebellion 3 （指反革命、反動派） counterrevolutionari...
  • 饋 : 動詞（饋贈） make a present of
  • 網 : Ⅰ名詞1 （捕魚捉鳥的器具） net 2 （像網的東西） thing which looks like a net 3 （像網一樣的組織或...
  • 路 : 1 （道路） road; way; path 2 （路程） journey; distance 3 （途徑; 門路） way; means 4 （條理） se...
  • 穩定 : 1 （使穩定） stabilize; steady 2 （穩固安定） stable; steady 3 （物質的性能不易改變的作用） stabi...
  • 網路 : 1. [電學] network; electric network2. （網） meshwork; system; graph （指一維復形）; mesh
  1. Output can be obtain, next we use our designed the wavelet soft threshold to select result of the wavelet transform, finally, we give the selected result reversal wavelet transform. it is obvious : the wavelet soft threshold is important to improve the quality of the gray image processing. i give the donoho wavelet soft threshold a modified value method, which has a relation with ratio of signal - noise. i made full use of discrete hop field single feedback neural network, and nonlinear steady of automatic system at last, i obtained a steady limited ring, give the energy function an order differential a optimal

    我的思路是：改造現有圖形結構，先建立能反映信噪比大小且含待定參數k的表達式，然後通過離散型h0pfi舊單層反饋神經網路，再結合前邊的混合濾波器構成一個非線性控制系統，寫出對應的網路函數，利用相平面法和李雅普諾大穩定性的判據，得到一個穩定的極限環，從而確定出參數卜的范圍，進而再對原來的小波軟閾值進行修正，用修正後的值作為小波閾值。
  2. This paper is focused on estimating the domains of attraction of equilibrium points for hopfield neural networks with delays and stabilizing a class of time - delays neural networks via standard feedback control

    本學位論文主要研究了時延hopfield神經網路平衡點吸引域估計以及通過標準反饋控制使一類時延神經網路穩定化。
  3. Chapter 4 discusses how to stabilize a class of time - delays neural networks via standard feedback control ; this kind of neural networks provides a unified view of several well - known neural networks ( such as hopfield neural networks and cellular neural networks ) with discrete delays or distributed delays. a stability criterion is given by using the lyapunov method. all the results obtained in this chapter are stated in simple algebraic forms so that their verifications and applications are straightforward and convenient

    通過使用lyapunov方法，我們得到了一類時延神經網路經過標準反饋控制后的穩定條件，這類神經網路涵蓋了幾種著名的神經網路，如hopfield神經網路、細胞神經網路，同樣，本章所得到的結論也是簡單的代數表達式，使用非常方便，最後在用計算機通過做數值實驗對這些結論進行了驗證。
  4. Finally, a feedback control system of neural network was designed and a special learning method was produced to train the neural network which was applied in the non - linear model of semi - active suspension. the result of test showed ride comfort and handling was improved preferably after the control, and the semi - active suspension system harmonized the vehicle performance with the controller

    最後，設計了神經網路反饋控制系統，採用一種特殊學習（直接學習）方法對其進行訓練，並將其應用於半主動懸架非線性模型的模擬驗證，通過對多種路面激勵輸入條件下的模擬分析表明：該神經網路反饋控制系統可以較好地提高車輛的乘坐舒適性和操縱穩定性，採用這種神經網路反饋控制的半主動懸架，可以較好地協調車輛性能。
  5. With regard to the flow regulation of the best - effort traffic, the controllable traffic in high speed computer communication networks, the present paper proposes a novel control theoretic approach that designs a proportional - integrative ( pi ) controller based on multi - rate sampling for congestion controlling. based on the traffic model of a single node and on system stability criterion, it is shown that this pi controller can regulate the source rate on the basis of the knowledge of buffer occupancy of the destination node in such a manner that the congestion - controlled network is asymptotically stable without oscillation in terms of the buffer occupancy of the destionation node ; and the steady value of queue length is consistent with the specified threshold value

    本文從控制理論的角度出發，針對計算機高速網際網路中最大服務交通流即能控交通流的調節問題提出了一種基於多速率采樣的具有比例積分（ pi ）控制器結構的擁塞控制理論和方法，在單個節點的交通流的模型基礎上，運用控制理論中的系統穩定性分析方法，討論如何利用信終端節點緩沖佔有量的比例加積分的反饋形式來調節信源節點的能控交通流的輸入速率，從而使被控網路節點的緩沖佔有量趨于穩定;同時使被控網路節點的穩定隊列長度逼近指定的門限值。
  6. This dissertation presented two new methods of robust adaptive track control for a class of mimo strong nonlinear system with external disturbance. one method makes use of taylor approximation principle to linearize the mimo strong nonlinear system at the ideal equilibrium point, meanwhile external disturbance is considered, and then designs two on - line neural network controller respectively, which can dynamically compensate the high order items of taylor series and the control signals at ideal equilibrium point under the drive of state error between linear and nonlinear system. a linear feedback controller obtained by pole assignment and two on - line neural network act on the practical mimo high nonlinear system together, guaranteeing the whole system robust stable and tracking the specified signal ; the other method designs three on - line neural networks for this class of system

    本文對於一類含有外部擾動的多輸入多輸出（ mimo ）強非線性系統，提出了兩種新的魯棒自適應跟蹤控制方法，第一種利用了taylor近似的原理，在考慮了外部擾動的情況下，將mimo強非線性系統在理想平衡點處線性化，分別設計了兩個在線神經網路控制器，在線性和非線性系統之間的狀態誤差驅動下動態補償系統的taylor近似高階項及理想平衡點處的控制信號，滿足極點配置方法的線性反饋控制器和兩個在線神經網路聯合作用於實際的被控mimo強非線性系統，在保證整個系統魯棒穩定性的情況下，能夠跟蹤給定的指令信號；另一種方法是針對這類系統設計了3個在線神經網路，分別實時抵消這類非線性系統中的非線性部分、與控制量耦合的非線性項以及外部擾動，使得受控系統的輸出可以完全跟蹤給定輸入參考信號。
  7. Based on the theory of passive system, we studied the essential conditions, by which chaotic dynamical system was equivalent to passive system. through theoretic proving, we found that using state feedback could make the passive system stable. based on passive equivalence theory, we proved that weakly minimum phase nonlinear system and minimum phase nonlinear system transformed by chaotic system having relative degree 1 could be globally asymptotically stabilized by smooth state feedback

    介紹了無源系統的基本性質及其意義，利用無源性網路理論，分析並推導了一般的混飩動力學系統等效為無源系統所必需的基本條件，從理論上證明了無源系統的可控性? ?利用簡單的狀態反饋即可實現無源系統的穩定控制，從而實現了將最小相位混飩系統及弱最小相位混」飩系統等效為無源系統，即構造混飩系統的控制器，將混飩系統配置為無源系統，實現混飩系統的穩定性控制。
  8. For this reason, theoretical study of neural dynamics has advanced rapidly in recent years. in this dissertation, we investigate the stability, bifurcation and chaotic phenomena of feedback neural networks including hopfield network and cellular neural networks ( cnns )

    本文對反饋神經網路（包括hopfield網路及細胞神經網路）的穩定性、極限環以及混沌進行了研究，主要工作概況如下：研究了細胞神經網路（ cnn ）的全局指數穩定性。
  9. As a part of the project, some contents, problems and recent researches on networked control system are introduced in this paper first. in order to reduce the occupation of network bandwidth, a method which finds the maximum transmit time can guarantee the stability of discrete control system is presented. for the sake of studying the network ' s delay influence on control system, a networked control system experiment software scheme is put forward in the last part of the paper

    文中介紹了網路控制系統的一些基本概念、問題及目前的研究成果，提出在採用模型狀態反饋控制律並考慮網路延時情況下，保證離散網路控制系統穩定的最大通訊間隔的選取方法，並研究了建模誤差對最大通訊間隔的影響，介紹了通過預報的手段減小網路延時對控制系統影響的方法。
  10. With switched control system theory and robust stability theory, the sufficient conditions for the asymptotic stability criterion of ncs with multi - packet transmission are obtained, and the method to design a periodically dynamic output feedback stabilization controller is firstly put forward in this paper

    利用切換系統理論和魯棒穩定性理論，得到多包傳輸網路控制系統的漸近穩定性判據，並首次提出周期動態輸出反饋鎮定控制器的設計方法。
  11. In chapter 6. the asymptotical stability for asymmetric discrete time recurrent neural networks is investigated. finally in chapter 7

    第六章對時間是離散但狀態是連續的離散反饋神經網路的漸近穩定性進行了深入的研究。
  12. In order to get the stability of model - based networked control system with output feedback and transmission delay, we use a state observer and an inner model to estimate the states of the plant controlled between the sampling times, and the knowledge of the system construction and state substitutions at sampling times

    摘要為研究基於模型的輸出反饋網路控制系統在傳輸時延情況下的穩定性，以得到固定時延系統采樣周期的最大波動范圍，在系統中，採用狀態觀測器及內設模型估計采樣時刻之間被控對象的狀態，並充分利用系統結構和在采樣點狀態更新的信息。
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