神經連合 的英文怎麼說

中文拼音 [shénjīngliángě]
神經連合 英文
commissure
  • 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
  • 連 : Ⅰ動詞1 （連接） link; join; connect 2 （連累） involve （in trouble）; implicate 3 [方言] （縫） ...
  • 合 : 合量詞（容量單位） ge, a unit of dry measure for grain （=1 decilitre）
  • 神經 : nerve; nervus
  • 連合 : coalesce; inosculation連合處 commissure; 連合分佈 joint distribution; 連合活字 logotype; 連合線 linea commissural
  1. Marine diesel union fuzzy neural network model can not only reflect the fuzzy character and logicality of main engine, but also avoid the joints between irrelevant parameters, simplify the network structure, and decrease the calculation. 2

    船舶柴油機組合模糊神經網路模型可以反映主機系統的模糊特性和邏輯特性，簡化了網路結構，避免了無關性能參數之間的連接，減少了計算量； 2
  2. In addition, many other problems also exist in hardware neural network, including error problem, learning mode, parallel architecture, and also neural network inner linking problem, hidden layer and the realization of the multiplicator and etc. for instance, error problem : hardware neural network employs the limited precision, and will inevitably bring limited precision error

    另外，硬體實現神經網路還存在誤差問題，學習方式，并行結構等方面的問題，還有神經網路內部的連接問題，隱層及乘法器的實現等等。如誤差問題，硬體實現神經網路使用的是有限精度，不可避免的會產生有限精度誤差，選取合適的精度，才能既適合空間的要求，又避免對網路的實現產生一定的影響。
  3. It is very important to estimate the basic parameters in helicopter preliminary design. neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods. however, there are some difficulties in using nn, e. g., how to select a proper network structure and the number of hidden layers. in this paper, structure and connection weight of a three - layer nn are optimized by genetic algorithm, and the optimized network is applied to helicopter sizing. the proposed method can not only give an optimal nn structure and connection weight, but also reduce the prediction error and has the capability of self - learning when the latest data are available. furthermore, this method can be easily applied to helicopter design systems

    在直升機初步設計階段估算其基本參數是很重要的.神經網路的通用性和精度比傳統的估算方法有更多的優勢，但是在應用神經網路時存在如何選擇合適的網路結構和隱層節點數目等一些困難.應用遺傳演算法優化三層神經網路結構和連接權重，並將優化得到的網路應用於直升機參數選擇中.該方法不但可以給出一個最優的神經網路結構和連接權重，而且降低了估算誤差，具有及時應用最新數據學習的能力.此外，該方法易於在直升機設計系統中得到應用
  4. 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
  5. To solve these problems respectively, the color space transformation and bp neural network are firstly used to realize the classification and threshold processing of images. then the images processing including thinning, interval linking, code word chaining, seed filling, boundary fitting is performed well by some methods in mathematical morphology and computer graphics and interpolation in numerical value analysis

    為了逐一解決這些困難，運用了色彩空間變換以及bp神經元網路的方法對圖像進行分類和閾值處理，利用數學形態學和計算機圖形學以及數值分析中的插值等方法對圖像進行了細化、間隙連接、鏈碼、種子填充、邊界擬合等處理。
  6. The program of data processing in determination of percent released of pharmaceutical preparation was developed ; two modules included in this program are connected but independence each other, one module calculate percent released, one module regress equation ; determination of percent released of pharmaceutical preparation, comparison of released curve in one reference frame and modeling mathematics model were realized by running this program. the program of formulation optimization based on artificial neural network was compiled to solve the nonlinear problem in formulation optimization. provided parameters were used to predict the released amount of a set of formulations

    簡便，其計算結果與現有其他程序計算結果基本一致：開發固體制劑體外溶出試驗數據處理程序，程序運行時分為計算累積釋放百分率和優選最佳數學模型兩個相互連接又各自獨立的環節，實現了累積釋放百分率的自動計算，同一坐標系下釋放曲線的直觀比較，常用數學模型的擬合；開發基於人工神經網路的處方優化系統，解訣處方優化這一多目標、非線性優化問題，利用符合擬合精度的訓練結果預測給定處方的釋放度，預測結果與實驗結果基本相近。
  7. In order to find out a novel fuzzy inference algorithm being superior to cr1 algorithm and a novel fuzzy neural network, the author deduces nine kind of triple i algorithms by nine fuzzy operators. further more, the author compares these algorithms with the ordinary intuitional rules respectively and gives a conclusion that rl - type triple i algorithm is rather more closely to the intuitional rules. because fuzzy neural networks require the conditions of continuous and differential on membership functions of fuzzy sets and fuzzy operators of fuzzy inference, by means of comparison study, the author obtains a conclusion that the fuzzy neural networks with production operator and cr1 inference algorithm are very fit to study the problem of control

    為了找出優于cri演算法的模糊推理方法和新型模糊神經網路，本文首先對常用九種模糊運算元給出了具體三i演算法，並從模糊推理的另一個方面，考察了各種演算法對日常直觀模糊推理規則的貼近程度，得出「 r _ l型三i演算法貼近日常直觀推理規則」這一結論；同時，考慮到模糊神經網路要求「網路輸出保持對模糊運算元和隸屬函數連續性、可微性」這一特性，通過比較研究，得出利用乘積運算元和cri推理的模糊神經網路最適合控制問題。
  8. 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。
  9. Signal layer represent links between the nerve cells, knowledge layer represent rules and reasoning of expert, conception layer is the medium layer and connect signal layer and knowledge layer, therefore integrated symbol computing ability of es with link features of ann into one body to make brain model more intelligent

    刺激層體現神經元的連接，知識層體現專家的規則、推理，從而將專家系統的符號計算和神經網路的連接主義兩者有機的結合，並在其基礎上構建了形體的表徵模型、推理方法，實現了形態構成知識的產生，為人腦模型的「智能」能力的實現和應用奠定了基礎。
  10. According to the special characters of a multi - roll cold tandem mill, a rolling force prediction model based on fuzzy algorithm and cerebellum model articulation controller ( cmac ) combined with the traditional model was designed to improve the precision of rolling force prediction

    摘要針對寬帶鋼多輥冷連軋機組特點，為提高軋制力的預報精度，在結合傳統軋制壓力模型的基礎上把模糊演算法和神經網路有機結合，設計出基於模糊小腦模型神經網路的多輥冷連軋機軋制力預報模型。
  11. When estimate the connecting relation among nodes, we utilize the matching relation between enlarged neural network and xor function. this is a learning process and it is a dynamic process with ceaseless game

    在判斷節點間的連接關系時用擴大了的「神經網路」擬合異或函數，這是網路的學習過程，也是一個不斷進行博弈的動態過程。
  12. Fusion algorithms are designed at feature extraction level and matching score level, by concatenating feature vectors, and integrating the matching scores using an adaptive neuro - fuzzy inferencesystem ( anfis ), respectively

    最後在特徵提取層和匹配值層設計了融合演算法，分別使用了向量連接法和自適應模糊神經推理系統（ anfis ） 。
  13. Thirdly, considering the characters of bp neural networks which is good at local minimum and bad in global optimization and the feature of ga neural networks which is bad in local minimum and good at global optimization, the paper proposes a new algorithm combined ga with bp, referred as to hybrid intelligence learning algorithm, which is applied to the problem optimizing the connection weight of the feedforward neural networks

    第三，針對bp神經網路局部搜索能力強、全局搜索能力差和基於遺傳演算法的神經網路全局搜索能力強、局部搜索能力差的特點，本文提出了一種集bp演算法和遺傳演算法優點為一體的混合智能學習法，並將其應用到優化多層前饋型神經網路連接權問題。
  14. Therefore reconstruction of nerve continuity is an effective treatment to prevent and cure neuromatic stump pain

    重新建立殘端神經連續性的各種手術，無論從預防還是治療的觀點出發，應該都是合理而有效的。
  15. 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。
  16. Application of bp neural network and spring equation to thickness prediction in aluminum hot tandem rolling

    神經網路和彈跳方程在鋁熱連軋厚度預報中的綜合應用
  17. On the basis of kineto - elastodynamics ( ked ), modern control theory and neural networks ( nn ), this dissertation studies, in a systematic way, the theory and the methods of the nn based active vibration control of flexible linkage mechanisms whose flexible links are incorporated with piezoceramic actuators and strain gauge sensors

    本文首次將機構運動彈性動力學、現代控制論及神經網路理論相結合，以具有壓電陶瓷作動器與電阻應變計傳感器的平面彈性連桿機構為研究對象，系統地開展了基於神經網路的彈性連桿機構振動主動控制的理論、方法與實驗研究。
  18. 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。
  19. Although most musculoskeletal injuries are not life - threatening, open fractures or fractures accompanied by severe blood loss and fractures that damage vital organs are medical emergencies requiring immediate attention

    直接由骨折引起的並發癥包括與骨連接、無血管性壞死和骨感染相關的問題。間接並發癥則與血管和神經損傷有關，會導致出現間室綜合征、靜脈血栓、脂肪栓塞、外傷性或低血容量性休克等。
  20. In terms of our results, it is hypothesized that in the central auditory system when the sound information is conducting through continuous synaptic clefts, there are interactions and integrations occurring between the ascending and corticofugal descending pathways with neural inhibition or facilitation so as to realize the neural integration that diverging or converging sound information with new forms, which ensures the neurons tune the sound information with biological significance

    據此推測，當神經元的信號在不同聽中樞結構中通過連續的突觸連接時，上行性或離皮層下行性神經抑制或神經易化通路之間在不斷地發生相互作用與整合，從而使得聲信息以新的方式分散或聚合，實現新的神經整合過程，以保證神經元調諧有生物學意義的聲信號。
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