神經元模型 的英文怎麼說
中文拼音 [shénjīngyuánmóxíng]
神經元模型
英文
neuromime-
Both input and output of the networks are cither procedures or functions. procedure - type ' s inputs to networks relax synchronization instantaneous limit on inputs in the traditional neural network models
過程式輸入放寬了傳統神經元網路模型對輸入的同步瞬時限制，是傳統神經元網路在時間域上的擴展，是更一般化的人工神經元網路模型。Firstly, second harmonic component ratio and dead angles of two phase inrush ' s dispersion in three - phase transformes are acted as input variable. secondly, the method applies improved algorithm based on the original algorithm of multi - layer forward back propagation network, that is to say, adding last variational effect of weight value and bias value to this time and making use of variable learning rate. at the same time, this method also adopts dynamic form in the number of hidden floor node
首先，文中將三相變壓器兩相涌流差流的二次諧波含量比和間斷角作為網路的輸入變量；其次，利用對原有bp網路訓練演算法基礎上的改進型演算法（即在計算本次權值和閾值的變化時增加上一次權值和閾值變化的影響以及採用變學習率，與此同時隱含層神經元個數採用動態形式） ，通過樣本訓練使網路結構模型達到最優。In term of the control mechanism between tp and te, possibly, this special control method will provide the control theory some spark. based on the research and conclusion of the frog visual behavior, in term of the control mechanism among the tp, te and endbrain area, the author has done a detailed system analysis and use the computer 3d to simulate the frog vision behavior. this kind of visual behavior model could be taken as a good reference to study the formation of the vision and its characteristics
文中通過對青蛙視覺行為數據的細致整理和總結，根據丘腦-前頂蓋（ tp ） ~ 1 、頂蓋~ 2和端腦區域里神經元集團之間的相互作用機制並結合具體的視覺行為，做了詳細的系統分析，並在此基礎上，使用計算機3d技術對青蛙視覺行為進行了模擬，這種直觀的視覺行為模型能夠為我們進一步研究視覺的形成和特點提供良好的依據和借鑒。In present study, single fibre recording in vivo from dorsal root on chronically compressed drg model was used. we analyzed the characters of isi series of oscillation firing of type a neurons induced by veratridine, an inhibitor of inactivation gate of sodium channel. so we can establish a basis for understanding the relationship between the inactivation gate of sodium channel and the firing pattern, so as to explore the relationship between the firing pattern and pain
本研究在大鼠背根節慢性壓迫模型上，利用在體單纖維記錄方法，觀察與分析na通道失活門抑制劑藜蘆堿引起受損背根節a類神經元放電isi序列發生的變化特徵，為了解na通道失活門與放電型式的關系以及進一步探索放電時間型式與疼痛的關系奠定基礎。Methods : hyperosmotic pressure animal model was established by administering 3 % sodium chloride as drinking water to rats or increasing osmotic pressure of the culture medium. osmoregulation positions in the brain, reciprocal projection pathways between the medullary visceral zone ( mvz ) and supraoptic nucleus ( son ) or hypothalamic paraventricular nucleus ( pvn ), oscillation of intracellular calcium in cultured neurons and astrocytes were studied by means of anti - fos, glial fibrillary acidic protein ( gfap ), tyrosine hydroxylase ( th ) or vasopressin ( vp ) multiple imrnunohistochemical staining, immuno - electronic microscope, wga - hrp retrogradely tracing and cell culture methods. results : ( 1 ) fos positive neurons within the mvz, parabrachial nuclei, locus ceruleus, pvn, son, subfomical organ increased markedly
方法：通過給予大鼠飲用3氯化鈉或提高培養基滲透壓濃度的方法復制高滲刺激模型，主要採用抗fos 、膠質原纖維酸性蛋白（ gfap ）和酪氨酸羥化酶（ th ） （或加壓素? vp ）免疫組織化學多重染色、免疫電鏡、 wga - hrp束路追蹤結合免疫組織化學多重染色、細胞培養等實驗方法，系統觀察了中樞參與滲透壓反射的調控部位、下丘腦視上核（ son ）神經元? ast超微結構的變化、延髓內臟帶（ mvz ）和son及下丘腦室旁核（ pvn ）之間往返投射通路和神經元的性質及其與ast的關系、培養神經元和ast內鈣波的變化。Three valued logic neuron model and its reasoning
三值邏輯神經元模型及推理By analyzing limitation of the traditional neural network, this paper presents intelligent neuron model based on linear independently function. the knowledge storing capacity of the intelligent neuron is analyzed
在分析傳統神經網路缺陷基礎上，運用線性獨立函數構建了智能神經元模型，並對這種神經元的知識存儲能力進行了理論分析。Applied in license plate segmentation problem, a new segmentation method of automobile license plate based on wavelet transform and neural network is pointed out [ 71 ]. 2 ) phase of image feature extraction : combined with the feature extraction of structural and statistical method, a method of image character feature extraction based on wavelet and moments analysis is presented [ 74j. 3 ) phase of image classificaton [ 73 ] : after investigation on intelligence recognition technology, the paper puts forward basic structure of recognition machine ' s model, and makes a primary research of basic structure and design method, then makes research of the multi - character method
並應用於車牌分割問題，提出基於小波與神經元模式識別的車牌圖像分割方法； 2 ）特徵提取階段：將結構特徵提取方法和統計特徵提取方法的緊密有機結合，提出一種基於小波和矩的車牌圖像字元特徵向量提取方法； 3 ）分類識別階段：對智能識別技術進行研究，提出智能識別機的模型結構，對識別機的基本層次結構和設計方法進行初探；並針對多特徵方法進行一定的研究；本文提出的基於模式識別的圖像處理方法對其他領域的圖像處理具有一定的參考價值。Firstly, the basic theories of artificial neural network are introduced, including neural cell model, the basic structure of artificial neural network and the study methods. the essential of bp network with function approximation and rbf network and the performance of technology are analyzed. the algorithm of bp and rbf networks are also studied
論文首先闡述了神經網路的基本理論，包括神經元模型，神經網路的基本結構和神經網路的學習方法;分析了具有函數逼近能力的bp網路和徑向基函數（ rbf ）網路實質、技術實現問題，並研究了bp和rbf網路學習演算法。Besides, we show the method and result in the research of the heart rate variability. it is proved that the nonlinear analysis is much more effective in the clinical diagnoses of heart disease. by the end of this dissertation, we list some problems for our future works including chaos in discrete time ~ varying systems, srb measures of the chaotic map in the sense of marotto, complex dynamics of both h. h. model and cou - pled integrate - and - fire models, strange attractors in h6non systems with classical parameters
在本文的第五章中，我們給出了一類一維時滯泛函微分方程穩定性的判別法，而這一方程本身可以用來刻畫連續的具有動態閾值的神經元模型；此外，我們介紹了非線性指標在心律變異中的具體應用與部分的分析結果，以進一步說明非線性分析在心律變異研究中的有效性和實用性Then, we give some basic information about the neuron model we studied which given by hodgkin and huxley
然後，我們給出所研究的模型? hodgkin - huxley （ hh ）神經元模型的一些基本知識。2. the basic theories of neuron model - free control are introduced, which includes the neuron model for control, the learning strategy and the neuron control method. 3
介紹了神經元非模型控制的基本理論和方法，包括面向控制的神經元模型、學習策略、神經元控制系統的一般結構和神經元非模型控制的基本方法； 3A survey of adaptive control, fuzzy control and neuron control is summarized, and the problems existing in neuron model - free control systems and its integrating with fuzzy systems are also discussed
綜述了自適應控制、模糊控制、神經元控制的發展和研究現狀，並就模糊神經非模型控制的研究提出了一些作者的觀點。In this case, the author puts forward to new aon - linear neural networks for classing - cc model and its network architecture
為此作者提出了新的用於分類學習的非線性神經元模型- - cc模型以及相應網路結構。Second, according to the characteristic of the instantaneous change of action potential accompanied by the nerve impulse, we use h - h equation to describe such change, and conduct simulation combined with sr theory
然後根據產生神經沖動時動作電位全或無式瞬時快速變化的特點，採用h - h方程作為描述這種變化的神經元模型，結合隨機共振理論進行了模擬研究。Besides stability, bifurcation and chaos in neural networks have receiving much attention recently. in this dissertation, we propose two neuron models with chaotic dynamics, which constitute chaotic neural networks that encompassed various associative and back - propagation networks
除了穩定性之外，極限環以及混沌也是神經網路動態行為研究的重點，本文構造了具有混沌解的兩種神經元模型，通過混沌神經元的耦合可以構成混沌神經網路。Fifthly, this paper proposes the model of three - rank chaotic neural network, its chaotic characteristic is simulated. the optimization parameter of non - line chaotic neural element model and neural network model with transient chaotic behaviors are discussed
建立了三階混沌神經網路模型，並對其混沌特性進行了數值模擬；模擬分析了非線性混沌神經元模型的混沌特性；探討了暫態混沌神經網路模型參數的優化選取。Based on fuzzy number nn, the model of fuzzy chaotic neuron is proposed in this paper, whose dynamics characteristics also have been analyzed thoroughly. the method how to build fuzzy chaotic neural networks ( fcnn ) with fuzzy chaotic neurons is also given
基於模糊數神經網路的實現方法，本文提出一種模糊混沌神經元模型，詳細分析了其特性，並且給出了構建模糊混沌神經網路以及確定混沌神經網路聯接權值的方法。After we present the concepts of " coherence resonance " and " stochastic resonance ", to further study the hh neuron model, we introduce some properties of the hh equation, for example, the threshold of neuron ' s exciting, the responses of neuron toward different stimulations
在介紹了「相干共振」和「隨機共振」的一些概念后，在hh神經元模型的基礎上，本文給出了hh方程的一些特性，比如說神經元的興奮有閾值，在受不同刺激時有不同的響應等。We, in chapter 4, comprehensively discuss the dynamics of discrete chaotic neural networks, including f the existence of fixed points, the stable, unstable dynamics of the fixed point, the saddle - node and period doubling bifurcations in singie neuron model, and chaotic dynamics of the networks. the proofs and de - ductions involve schauder fixed point principle, constructions of lyapunov func - tions, bifurcation theory, contraction map principle, and anti - integrable limit method
在本文的第四章中，我們首先介紹了離散混飩神經元、神經網路模型由來與具體的數學模型，依次給出了該離散神經網路的中不動點存在性與惟一性的分析：穩定性與不穩定性的分析；神經元模型的分枝分析；神經網路中馬羅陀意義下混3屯動力學的分析分享友人