除神經法 的英文怎麼說
中文拼音 [chúshénjīngfǎ]
除神經法
英文
unnerving-
Application of neural network in jarosite process of zinc hydrometallurgy
神經網路技術在濕法煉鋅礬法除鐵中的應用Other than paying attension to these areas during the operation, the author believes there are several points for the effective removal of cholesteatoma : 1 ) use of open or open - closed method for mastoidectomy ; 2 ) incision made over some safe site on the cholestratoma sac to remove its content beforehand, which will fascilitate the elevation of matrix after wards : 3 ) exposure of the fallopian canal in the tympanic cavity before lowering down the facial ridge ; 4 ) care be taken of pediatric cholesteatoma ; 5 ) good control of blood pressure and bleeding during the operation ; and 6 ) illumination
除了特別的注意這些部位外，開放腔或開放后再封閉的手術法，由外而內的將外耳道先行擴大以充分露出術野，大型膽脂瘤囊袋內容物先取出再予剝離，講求顏面神經嵴削低的技巧，以及對小兒例的警戒心，術中出血的控制和照明的良好等，均為防止膽脂瘤殘留的要訣。Since the possibility of malignancy can ' t be rule out, a laparoscopic adrenalectomy was performed uneventfully, and pathological findings proved to be a ganglioneuroma
由於無法排除惡性病變的可能，病人接受手術切除腫瘤，病理檢查證實是神經節神經瘤。Aim to eliminate the influences of backlash nonlinear characteristics, a second generation adaptive pid controller based on single neuron is given. the result of simulation and the debug of actual digital servo system shows that the controller can effectively get rid of the sustained oscillation of the system caused by the backlash characteristics, and can improve the system accuracy
隨后，採用改進型單神經元自適應pid控制器來消除間隙非線性對系統的影響，模擬結果表明所採用的方法能有效消除間隙特性引起的系統自振蕩，並且能夠提高系統的跟蹤精度。Via this neural network, we can eliminate those regions which contain no plate and then use color information to modify the correct region and find the accurate position of car plate finally ; 3 ) in the progress of recognition, we apply the structural alternative covering algorithm and only use some basic techniques to process the image
將構造性的覆蓋演算法應用於牌照的定位，在對這些區域進行分析后提取出各自的特徵並進行學習，構造出相應的神經網路，用來排除假的干擾區域，同時結合圖像的顏色信息來對前期的定位結果進行修正，最終得到正確的車牌位置： 3The algorithm can not only eliminate the influence of the cumulative errors of the photoelectric code recorder, but also it can satisfy the requirement of the real - time control. a direct inverse model controller of fuzzy neural network with changeable structure based on takagi - sugeno inference is presented and it is used to the motion control of mobile robot. in order to avoid the obstacles successfully, detection results from ccd and ultrasonic sensors are fused by a fuzzy neural network, which acts as an avoidance controller
包括移動機器人的融合自定位問題：移動機器人利用光電編碼器進行自定位，同時用擴展卡爾曼濾波器融合多個超聲波傳感器的測量值，採用回朔演算法將融合值用於復位光電編碼器，消除了光電編碼器累積誤差的影響，並能滿足實時控制的要求：並提出一種基於takagi - sugeno模型的變結構模糊神經網路直接逆模型控制器，並應用於移動機器人的運動控制；利用模糊神經網路避障控制器融合ccd攝象機與超聲波傳感器探測到的環境信息，以實現機器人的安全避障。The potential applications of amr include both civil and military communication, especially non - cooperative communications and communication confrontation, such as identifying signals, supervising signals, distinguishing interference, electronic confrontation, analyzing military threat, etc. on the basis of our analysis to the existing research on feature abstraction, the related feature abstraction methods are optimized in this paper, resulting several effective methods such as the feature abstraction based on transformation domain, stepped voltage level analysis, normalized carrier - free spectral energy analysis, squared signal and fourth powered signal analysis, etc. both the decision theory based on recognition algorithms and the artificial neural network ( ann ) based on recognition algorithms is analyzed, and the former is selected as it is more appropriate for this research
調制類型的自動識別廣泛應用於民用通信與軍用通信，尤其是對于非合作性通信、通信對抗，比如：信號確認、信號監控、干擾辨識、電子對抗、軟體無線電、電子救援、通信對抗、軍事威脅分析等。本論文在分析現有研究的基礎上，借鑒了已有的特徵提取方法，對相關調制類型特徵提取方法進行了優化，使用了一些有效的方法，如基於變換域特徵提取方法、梯層電平分析方法、剔除載波后的歸一化頻域能量分析方法、信號平方后的頻譜分析方法、信號四次方后的頻譜分析方法等。通過對基於決策理論和基於人工神經網路兩種識別演算法進行分析，本論文選擇了較適合的基於決策理論的識別演算法。The content of this paper is arranged as foll owing : chapter 1 introduces the concept of credit, credit risk and credit assessment, as well as the history and development of credit assessment ; chapter 2 introduces the history of ai technology, and the background of expert system and neural network. characters and disadvantages of expert system and neural network are presented respectively and the necessity of combining expert system and neural network is lightened ; chapter 3 shows the process of dealing with sample data, including the treatment of exceptional data and factor analysis, and puts forward the concrete framework of the mixed - expert credit assessment system ; chapter 4 introduces concept of object - oriented technology, and constructs object model and functional model after analyzing the whole system. it also illustrates the implementation of concrete classes by an example of rule class and the inference algorithm in the form of pseudocode ; chapter 5 introduces the structure of the whole system, the major functional models and their interfaces, and the characteristic of the system is also generalized ; chapter 6 summarizes the whole work, and points out the remaining deficiencies as well as the prospective of this method
本文具體內容安排如下：第一章介紹了信用、信用風險、信用評價的概念，回顧了信用評價的歷史、發展和現狀，並綜合各種信用評價模型，指出這些模型各自的優缺點：第二章簡單描述了人工智慧技術，著重介紹有關專家系統與神經網路的基礎知識，通過總結它們的優缺點，指出結合專家系統與神經網路構造混合型專家系統的必要性；本章還介紹了神經網路子模塊的概念，提出了混合型專家系統的一般框架與設計步驟：第三章對樣本數據進行處理，包括異常數據的剔除、因子分析等，提出了信用評價混合型專家系統的具體框架結構，介紹了系統知識庫的主要部分、基於優先級的正向推理機制的流程、以及基於事實的自動解釋機制的具體實現方法；第四章介紹了面向對象技術，進而採用面向對象對信用評價系統進行分析，建立了對象模型和功能模型，並在此基礎上，採用c + +語言以規則類為例說明系統中具體類的實現，用偽代碼的形式描述了推理的演算法；第五章描述了整個系統的結構，對系統主要功能模塊和界面進行了介紹，並總結系統的特點；第六章總結了全文，指出本文所構造系統存在的不足以及對將來的展望。On the basis of analysing multilayer forward artificial neural networks which based on back propagation algorithms and basic principles of the adaptive noise cancellation system, this paper sets up an adaptive noise cancellation controller based on artificial neural network, which is proved to be more efficient in the noise cancellation and has robust performance based on simulink of matlab at the end, this paper proposes some advices of model and algorithms
在對基於誤差反向傳播學習演算法的多層前向人工神經網路進行分析基礎上，結合傳統自適應噪聲抵消系統基本原理，建立了基於人工神經網路的自適應噪聲抵消器，經基於matlab的simulink模擬實例證明，具有很強的噪聲濾除能力和魯棒性。最後並提出了網路及演算法進一步改進的方法。Since 2000, a group of french urologists successfully performed radical prostatectomy with the advantages of better urethro - bladder anastomosis and neurovascualr bundle preservation which was provided by the laparoscopical magnified vision
自2000年開始，一群法國泌尿科醫師利用腹腔鏡之優點，成功地完成根除性攝護腺切除術，此手術可更清楚地完成尿道膀胱吻合術及勃起神經及血管之保留。Phases straight lines model and not straight lines model based on bp are used to correct the physical parameters and eliminate deflection. the least - square is used to calculate the efficiency of generators
在物理量校準中利用分段直線回歸和基於神經網路的非線性回歸，對模擬量進行了非線性在線校正來消除誤差；在發電機效率計算中利用最小二乘法實現了發電機效率回歸。Firstly, the paper, combining the characteristic of synchronous pulse bursts and inhibition with the modified pcnn model, presents a way of finding the foveation points in the images adaptively and effectively, and simulates the human vision system. secondly, pcnn is extended to pcnns, based on the properties of information couple and transmission, an algorithm that is used to fuse images of the same target got by several sensors to an image is presented to simulate the human vision system. thirdly, combining the properties of synchronous pulse bursts, capture, and transmission and competition of waves, the paper presents two ways of classification, one is an algorithm based on the properties of neuron to capture and inhibit to classify the data taking on any complex unlinear distribution robustly, the other is based on the restricted distance and modified of the former to remove the influence of inferior samples in classification ; fin ally, based on the accumulative difference pictures, and the forming and transmission of pcnn wave, selecting and controlling the direction of autowave by connecting the neighbouring neurons selectively, the paper presents a way to simulate the tracks of moving object and detect the moving direction
首先結合pcnn的同步脈沖發放和側抑制特性，提出了基於改進型pcnn的圖像凹點檢測演算法，該演算法是一種自適應而有效的圖像凹點檢測方法，並且較好地模擬了人類視覺系統；然後，結合信息傳遞和信息耦合特性，將pcnn擴展成pcnns （ pcnn網路群） ，提出了一種基於pcnns的圖像融合演算法，能夠將多個傳感器獲取的同一目標的圖像信息融合到一幅圖像中，有效模擬了人類視覺系統；另外，結合pcnn的同步脈沖發放特性、捕獲特性和波的傳播競爭特性，開拓地將pcnn用於模式分類中，提出了基於耦合神經元點火捕獲抑制特性的分類方法和改進的約束距離下的pcnn分類方法，前者可實現對樣本空間中任意復雜分佈訓練樣本的穩健非線性分類，而後者能夠消除訓練樣本中刺點對分類的影響；最後，結合累積差分圖像思想、 pcnn波的形成與傳播特性，通過各神經元之間連接取向來選擇與控制自動波的流向，將pcnn用於運動視覺分析中的運動軌跡模擬及運動方向檢測。Promote vlood cycle, alleviate pain to pain to eliminate waist sour backache, alleviation is exhausted, aim at because of take causing for a long time zhlmuscle ache, or slnce moving to cause zhi muscle ache, wlth vanious famous andprecious plant shrewd oll prescniption, stiff infltration promoes blood cycle into the regulation delight cantral nervous, belancsd homone and skin of human body, throughprofasslonal slcill, strengthen skin heelth, eliminate since muscle dd hams the function obstace that arouses
促進血液循環，減輕疼痛消除腰酸背痛，緩解疲勞，針對因久坐而造成之肌肉酸、痛，或因運動造成肌肉酸痛，採用多種名貴植物精油配方，強力滲透進人體肌膚，調節快感中軀神經，平衡激素，通過專業手法，促進血液循環，強化肌膚健康，消除因肌肉勞損引起的功能障礙。In the paper, the following main factors are studied, such as developing the expert knowledge - base based on the special knowledge of the explosive demolition of frame building, designing the object - oriented expert system of the explosive demolition of frame building, developing the neural network training example base based on projects, developing the forecasting mode of blast effects with matlab 6. 1, developing the expert system of explosive demolition of frame building with visual b 6. 0, carrying out the connection of the expert system and forecast mode. the system consisted of eleven functional modules, such as the input of initial parameters module, the choice of the blasting method module, the choice of blast mode module, the design of blasting parameters module, the design of charge module, the verifying blasting safety module, the calculating safety of tumble module, the design of detonating net module, the blast effects forecasting module and the calculating volume module
本文的研究內容有：以框架結構樓房拆除爆破領域的專業知識為基礎製作專家系統知識庫；設計一般面向對象的框架結構樓房爆破拆除設計的專家系統；搜集相關爆破工程實例製作用於爆堆效果預測神經網路訓練的樣本數據庫；選取適當的輸入輸出因素，用matlav6 . 1構建爆破效果預測神經網路模型；用vb6 . 0編程開發出框架結構樓房拆除爆破專家系統，並實現爆破效果預測神經網路模型和專家系統的鏈接。該系統由初始參數輸入、倒塌方法選取、倒塌方案確定、孔網參數設計、缺口形狀及參數、爆破安全校核、傾倒安全校核、爆破網路、爆破效果預測、工程量計算、計算設計說明書等十一大功能模塊組成。Methods since 1986, after resection of stump neuroma in 182 cases, nerve continuity was reconstru cted by means of venous bridge ( 77 cases ) ， nerve grafting ( 73 cases ) and anastomosis of nerve stumps ( 32 cases ), t o prevent neuroma formation
方法1986年起，在切除殘端神經瘤后，採用靜脈橋接法（ 77例） 、神經原位移植法（ 73例） 、兩神經殘端直接縫合法（ 32例）等重新建立神經連續性的方法，治療上臂殘端及手指殘端神經瘤性殘端痛182例。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。Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly
本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。In the design of four - bar linkages driven by motor, the mass - distribution is used to counteract the fluctuation of system and improve the performance. at the same time, this paper applies an adaptive neuron pid controller for nonlinear time - variable system. it efficiently lessens the fluctuation, accompanying with mass - redistribution
在電機驅動的平面四桿機構設計中，首先對機構進行質量平衡，這不但減小了速度波動，而且也簡化了狀態方程；再針對系統的狀態方程非線性、時變特性選用單神經元自適應pid控制器的方法，有效的消除了系統的速度波動。The classifier with ability of feature selection is studied to prepare for face cascade representation and to make it possible to detect and recognize face fast and accurately. finally, construction of an array of classifiers is researched, and an effective method to design classifiers of fast face detection and recognition with complex background is presented, which is able to radically discard redundant areas and realize a robust real - time face detection designed for complex background and recognition system with large face database. finally, a fast face detection and recognition system for images with complex background is proposed and implemented by combining face cascade representation and classifier design
首先研究了在人臉檢測和識別中常用的分類器，比如符號函數、最近鄰、神經網路、 svm 、 adaboost等，選擇了適合於人臉檢測和識別的分類器，並提出了結合pca特徵和rbf進行人臉姿態的判別方法：其次研究了具有特徵選擇功能的分類器發計，這為人臉的級聯表示提供了條什，也為快速準確的人臉檢測和識別提供了可能；最後，對組合分類器設計進行了研究，提出了適于復雜背景下快速人臉檢測和識別的有效分類器設計方案，這使得人臉檢測和識別能夠快速剔除不感興趣區域，為復雜背景下實時人臉檢測和大型人臉庫的快速識別提供了可能。( 2 ) a fuzzy - neural network multiple - variable control algorithm has been brought forward. it separately controls the two loops at the side of the boiler and at the side of the turbine, eliminates or reduces the coupling of each loop by the single - layer neural network
（ 2 ）提出了一種基於rbf神經網路的模糊神經網路多變量控制演算法，分別對鍋爐側和汽機側兩個迴路進行控制，並通過一個單層神經網路的協調級來消除和減小各迴路的耦合影響。分享友人