neuron model 中文意思是什麼
neuron model
解釋
神經元模型-
This thesis has studied the dynamic features of a class of the discrete - time neural network model of two neurons, such as the convergence and periodicity and etc. the function of the neuron signal transmission in this model, which belongs to three piecewise constant argument, indicates the following charactersif the signal of one neuron on the network is active between a and b, it will produce invariable encouragement effect on another neuron ; if the signal of one neuron is lower than a, it will produce invariable restrain effect on another one, if the signal of one neuron is higher than b, it will produce no effect on another one
本文研究了一類二元離散人工神經網路模型的解的收斂性及周期解的存在性等動力學特徵。該模型的神經元信號傳遞函數是三段常數不連續函數。這種信號傳遞函數表明如果某神經元的信號在a與b之間活躍，則它對另一個神經元產生恆定的激勵效果，如果某神經元的信號低於a ，則它對另一個神經元產生恆定的抑制效果，如果某神經元的信號高於b ，則它對另一個神經元不產生作用。 -
The model - free pid control method with neuron tuning gain and the neuro - fuzzy control method for a constant cutting force metal turning process system are proposed. the former method keeps the cutting force to be constant by using the neuron to change the pid controller gain on - line. the latter method construct the fuzzy neuron controller by combing the fuzzy controller and the neuron controller
針對具有非線性和不確定性的機械加工切削過程，提出了神經元增益自整定的pid控制方法和模糊神經元非模型控制方法，前者採用神經元來在線調整pid控制器的增益，後者將模糊控制器和神經元控制器相結合構成模糊神經元控制器，這樣當對象特性隨切削深度的變化而變化時，所設計的控制器能保持切削力恆定，使系統穩定並具有滿意的動態品質。 -
The neuron control method with self - tuning gain is proposed for a ph neutralization process. in this control system, the fuzzy t - s model is used to predict the control signal. the neuron controller gain is calculated according to the parameter estimation and experience formulas
針對具有嚴重非線性特性的ph中和過程，提出了一種模糊增益自整定神經元控制方法，這種方法採用t - s模糊推理估計下一時刻的控制量，並通過參數估計和經驗公式來計算出神經元控制器的增益。 -
To the level control problem of a spherical tank, two model - free control methods are proposed. in the former method, the takagi - sugeno fuzzy model is used to tune the neuron controller gain. in the latter method, the model - free control method using the neural network model proposed for nonlinear plants is presented
針對具有非線性特性的球形容器液位受控對象，從增益自調整和非線性補償兩個角度，分別提出了兩種非模型控制方法，前者採用t - s模糊模型對神經元控制器的增益進行在線整定，後者使用本文建立的非線性神經元網路對球形容器進行非模型控制。 -
Hi the aspect of symmetry analyzing to the hopfield model neural network with hebbian learning, we study on the dynamical behavior of the state space under the action of isometric transformation group g = z2 ? n, and prove the invariant property of the energy orientation ? / / " ) of the state space under the action of g. we find that the symmetry relationship of the network is sx - sw = sh when the active function of the neuron is odd, where sx is the symmetry of the patterns set x under hebbian learning rule, sh is the symmetry of the network and sw is the symmetry of the weight matrix w of the network
） s _ n為手段，研究了網路狀態空間在群g作用下各點的運動情況，證明了群g作用下的不變性。證明了當神經元的激活函數f為奇函數時， hebb法則下存儲樣本集x的對稱性s _ x 、網路對稱性s _ h以及連接矩陣對稱性s _ w三者之間滿足s _ x = s _ w = s _ h的關系；同時，我們還證明了：網路穩定態集vf同一s _ h軌道中的兩個穩定態的動力學行為（能量和吸引域大小）相同；兩個等距網路h和h 1 = g ? h ， （ ? ） g （ -
An edge detection model with neuron - like organization
一個具有擬神經組織的邊緣檢測模型 -
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。 -
2. an introduction of the basic principles of the neuron model - free control and the basic design methods of the fuzzy controller is given
介紹了神經元非模型控制的結構和基本原理及模糊控制器的設計的兩種基本方法。 -
Thus, we have deeply studied the applications of stochastic theory in protein motor and fhn neuron model, and obtained some important results, especially the opposing role of the amplitude and correlation strength in protein transport, the locked phenomenon in fhn neuron model, the dependence of the effect on initial condition, the phase transition and resonance in globally coupled neuron system
為此，我們對隨機理論在生物馬達蛋白和fhn神經模型上的應用進行了較深入的研究，取得了一些有重要意義的成果，特別是發現：漲落勢的幅值和關聯強度對蛋白輸運起著相反的作用；噪聲誘導fhn神經電位的鎖定現象；噪聲關聯導致雙穩系統對初始狀態的記憶功能；噪聲作用下全局耦合fhn神經網路的共振和相變現象。 -
Based on the hh neuron model, we investigate the effects of patch temperature on the spontaneous action potentials for finite size of membrane patch
在前面介紹模型的基礎上，本文考慮了溫度對有限大小膜面積的神經元系統的影響。 -
In this thesis, the investigations of the application of stochastic theory in protein motor and fhn neuron model are systematically reported, which include four aspects : effects of random potential on motor protein transport ; noise - induced transition in a fhn neural model ; stochastic resonance in a bistable system subject to multiplicative and additive noise ; coherence and stochastic resonance in a globally coupled fhn neural model
現在我們集中報導對隨機理論在生物馬達蛋白和fhn神經模型上的應用所進行的一系列的研究，主要有以下四個方面：漲落勢誘導生物馬達蛋白輸運；噪聲誘導fhn神經模型相變：噪聲關聯對雙穩系統隨機共振現象的影響；全局耦合的fhn神經網路的隨機共振和同步共振。 -
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。 -
3. the adapive fuzzy neuron model - free methods are proposed by the characteristics of fuzzy system and neuron system 4
針對模糊系統和神經元系統的特點，提出了自適應模糊單神經元的控制演算法。 -
From the points of view for practical uses, the theory and applications of fuzzy neuron model - free control systems are researched in this dissertation
本文從工程實際出發，對模糊神經非模型控制系統設計理論和應用進行了研究。 -
The iniegrating forms between a fuzzy system and a neuron model - free control system are investigated and presented for designing the fuzzy neuron model - free controllers
針對模糊控制系統和神經元控制系統的不足，探討了神經元非模型控制與模糊控制結合的可能性。 -
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； 3 -
A 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。 -
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
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