聯想神經網路 的英文怎麼說

中文拼音 [liánxiǎngshénjīngwǎnglù]
聯想神經網路 英文
aann
  • 聯 : Ⅰ動詞（聯結; 聯合） unite; join Ⅱ名詞（對聯） antithetical couplet
  • 想 : 動詞1 （思索） think; ponder 2 （推測; 認為） suppose; reckon; consider; think 3 （希望; 打算） w...
  • 神 : Ⅰ名詞1 （神靈） god; deity; divinity 2 （精神; 精力） spirit; mind 3 （神氣; 神情） expression; l...
  • 經 : 經動詞[紡織] （把紡好的紗或線梳整成經紗或經線） warp
  • 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...
  • 聯想 : associate; connect in the mind
  • 神經 : nerve; nervus
  • 網路 : 1. [電學] network; electric network2. （網） meshwork; system; graph （指一維復形）; mesh
  1. As for the representation of the individuated pattern - base, we introduces a new classification representation method based on multi - users and multi - topics, so as to make each profile only denote one user ' s one topic. this method makes it possible to express explicitly the user ' s interest. as for the creation of the individuated pattern - base, we adopt the hopfield neural network model, which has the function of ample association and remembrance and may be used to associate with the user ' s interest to create the initial individuated pattern - base

    對于個性化模式庫的表示，本文給出了一種多用戶多主題的分類表示方式，使得每個profile文件只表達一個用戶的一個主題，可以更清晰的表達用戶的興趣；對于個性化模式庫的建立，本文採用了機器學習中的hopfield神經網路模型， hopfield網路具有豐富的聯想記憶功能，可以用來對用戶興趣進行聯想，建立用戶的初始個性化模式庫；對于個性化模式庫的維護，採用了基於用戶反饋的學習方法。
  2. Based on cognition theory and information technology, the paper build a simulated brain model to aid creative design by integrated artificial intelligent, expert system, fuzzy logic, and knowledge mining based on database over internet. the brain model including a memory structure to save information and knowledge, and a thought strategy with some certain levels to guide activities, therefore, the intelligent activities such as learning, problem - solving and creative design could be treated as the process that utility memory in control of thought strategy

    人腦模型體系包括了在思維策略控制下的學習、設計問題解決、創新等活動，並以語義網路與神經網路結合研究並實現了知識記憶結構，在此基礎上研究了產品構成知識的生成技術，使模型可方便實現自學習、自組織、聯想存貯等特性。
  3. Recurrent associative memory network

    反饋型自聯想記憶神經網路
  4. Rotor fault diagnosis of induction motors based of a dynamic associative memory of chaotic neural network

    基於混沌神經網路動態聯想記憶的電機故障診斷
  5. Solving these problems does very much good to the practical application of shape recognition system

    以上問題的解決對應用聯想記憶神經網路形狀識別系統解決實際問題具有很大的意義。
  6. Data collected from mengda power plant have been used to train the model. unlike normal direct - method / indirect - method of heat balance, this model computes the boiler efficiency and main parameters needed for control in the boiler ' s operation efficiently by taking the advantage of neural network ' s inherited powerful co - relating ability, memorizing ability and the ability of mapping with nonlinear variables

    此模型不同於傳統的鍋爐效率計算方法（正平衡或反平衡方法） ，而是通過人工神經網路本身具有的強大的聯想功能和記憶功能以及對于非線性變量的映射能力，來計算鍋爐效率和鍋爐運行中需要調節的一些主要參數。
  7. To improve the dynamical property and decoupling capability for a class of multivariable nonlinear systems with strong coupling, based on the principle of decoupling and neural network, a cascade - connected self - adaptive fuzzy - neural network decoupling controller is proposed

    摘要為提高多變量、非線性和強耦合系統的動態特性和解耦能力，根據解耦原理和神經網路思想，提出一種兩級串聯結構的自適應模糊神經網路解耦控制器。
  8. In order to overcome problems arisen from the application of x fluorescence analysis into complex spectrum produced by archaeological ceramic fragments with multi - element, low content and thick ground, we have employed the artificial neural network into the research of x fluorescence archaeology and conducted three kinds of research works. as the first one, we have applied the linear olam network ( optimal linear association memory network ) and the non - linear bp network ( back - propagation network ) respectively to analyze the complex x fluorescence spectrum of archaeological samples, and taken both results of spectrum analysis to compare with each other. the second, the method of pattern recognition of bp network was tentatively used to perform intelligent identification of production places of these archaeological samples

    針對科技考古中對大量考古陶片進行產地研究時x熒光分析對多元素、低含量、厚基底考古陶片產生的復雜譜分析的問題，將人工神經網路引入x熒光考古中，進行了三方面的研究工作：一是用線性olam網路（最優線性聯想網路）和非線性bp網路（誤差反傳導網路）分別對考古樣品的x熒光復雜譜進行解譜，並比較二者的解譜效果；二是用bp網路模式識別方法對考古樣品的產地進行智能識別；三是為了提高網路運算的可靠性和減小基體效應及電噪聲的干擾和影響，研究並提出了三種網路學習前的譜數據預處理方法。
  9. In this paper an artificial neural network ( ann ) approach, which is based on flexible nonlinear models for a very broad class of transfer functions, is applied for multi - spectral data analysis and modeling of airborne laser fiuorosensor in order to differentiate between classes of oil on water surface

    由於ann方法適合於處理非線性系統，具有自組織、自學習、自適應和聯想能力，故通過對樣本反復訓練，能辨別各類樣本特徵差異，本論文的核心工作就是將人工神經網路（ ann ）的方法應用於激光遙感光譜數據的智能分析。
  10. Then, a practical approach of software quality evaluation based on this model is given out which uses the network method of nerve and combines the associative memory model with the expert judge and fuzzy appraisal according to the gradient theory. and a program of this approach is compiled using c #. net

    然後，根據梯度理論，應用神經網路方法將聯想記憶模型與專家評判、模糊評價相結合，給出一個基於此模型的軟體質量評價的實用方法，並用c # . net對此評價方法編程實現，最後通過實例來說明此方法。
  11. 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。
  12. Neural network is applied in design of blast parameter, which is not needed the trim and sum up of engineer and knowledge of expertise. what are needed is some succeed examples and stylebooks to train the system. to some knowledge, which is expressed by implication, at the same time to acquire knowledge, much knowledge in the same question were showed in the same network

    採用神經網路進行爆破參數設計不需要知識工程師進行整理、總結以及消化領域專家的知識，只需要用領域專家解決問題的實例或範例來訓練網路；在知識表示方面，採取隱式表示；在知識獲取的同時，自動產生的知識由網路的結構和權值表示，通用性強，便於實現知識的自動獲取和并行聯想推理。
  13. Based on the neural network structure in the paper, the object - oriented knowledge representation thought about neural network is deeply discussed and this paper trys to realize it with the neural network structure. to some extent, it is realized, but not mature, this paper just puts forward an idea, and gives some sugestions. at last, the paper prospects the coming researching work

    目前來看，以文中的網路結構，只能一定程度的實現這一思想，因此，在展望中希望能夠進一步完善這種組建神經網路的思路，比如，可以採用結合異聯想神經網路（ bam ）來實現對象屬性空間的轉移，從而建立對象屬性之間的推理機制。
  14. The paper mainly did the dissemination of error neural network ( bp ) research and gave recommendations on ways to improve bp algorithm. by using better diagnostic techniques with the neural networks legend, memory and reasoning functions and tolerant nature, robustness and good nonlinear, it can better realized the fault

    主要對誤差後向傳播神經網路（ bp ）進行研究，提出了改進的bp演算法，利用神經網路的聯想、記憶和推理功能以及容錯性、魯棒性和很好的非線性映射能力等特點，更好地實現故障診斷。
  15. 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。
  16. In industrial the temperature system is classed large nonlinear system. with associative memory neural network as identification and fuzzy neural network as control established model reference adaptive control system, succeeded realized single dealing control. model reference adaptive control system supplied new method for other lager nonlinear system such as flux, stress and fluid system

    溫度控制系統是典型的非線性大滯后控制系統，根據本文提出的聯想記憶神經網路辨識器，與模糊神經網路控制器相結合，建立模型參考自適應控制方案，成功的實現了對單腔電阻加熱爐的控制，模型參考自適應控制方案可以向其它大滯后非線性特性的過程式控制制參量（如流量、壓力、液位等）推廣。
  17. In 1987, since b. kosko defined the ‘ max - min ’ neural networks as the fuzzy associative memories, the research has been attracted many scholar ’ s attention. fuzzy associative memories models integrate the advantages of both fuzzy systems and neural networks in dealing with information

    1987年， kosko提出了基於max - min模糊運算元對的模糊聯想記憶網路，首次有機地將模糊系統與神經網路結合起來，這樣做兼有兩者處理信息的優點。
  18. Neural network not only has the ability of dealing with complex pattern, associating, extrapolating and memorizing, but also has strong ability of self learning. it can catch up on the fault that heuristic rule can ’ t make diagnosis conclusions because of its noncompleteness. so neural network is appropriate to the fault diagnosis systems

    神經網路不但具有處理復雜模式及進行聯想、推測和記憶功能，而且還有很強的自學習能力，能克服由於啟發式規則的不完備而無法做出診斷結論的缺陷，因而它非常適合應用於故障診斷系統。
  19. In this paper, the artificial neural networks are considered as a structure set of the neurons. based on this point of view, we make a comprehensive and deep researching on the hopfield model neural network of associative memory with hebbian learning in three aspects, i. e., analyzing, describing and computing of the symmetry of the system, thus discovering the storing mechanism of the hebbian learning rule. which give a deeper understanding to the associative memory mechanism of artificial neural network

    本文將人工神經網路視為神經元的結構集，並從這個基本觀點出發，從三個方面，即對稱性的分析、表示以及計算，對hebb型的離散hopfield模型神經網路進行全面的、深入的研究，揭示了hebb法則這種特殊的存儲規則的機理，並以此來達到加深對整個網路的聯想記憶機理認識的目的。
  20. In short, through researches the author discovers chaotic neural networks having tremendous preponderance in the field of intelligent message treatment, particularly of separation of superimposed pattern, many - to - many associations and successive learning

    總之，經過本文的研究發現：混沌神經網路在信息處理特別是聯想記憶包括分離疊加模式、多對多聯想和連續學習方面具有巨大優勢。
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