hopfield neural network 中文意思是什麼
hopfield neural network
解釋
霍普菲爾德神經網路-
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。 -
Generalized discrete hopfield neural network and heuristic algorithm
廣義離散神經網路模型及啟發式演算法 -
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 （ -
To overcome the defaults of traditional algebra - based methods such as high gain, repetitive computation and disability of real - time solution, in this paper, we propose a novel method design of observers using hopfield neural network
為了克服傳統上用代數方法設計狀態觀測器時增益過大、重復計算以及不能滿足適時性等缺點，本文提出了一種基於hopfield神經網路的觀測器設計方法。 -
Traveling salesman problem is combinatorial optimization problem in graph theory, it has npc computation complexity, and lots of problem can transfer to traveling salesman problem. the computation of tsp is analyzed, then the hopfield network method for solving tsp is given, at last we solve 10 - citys traveling salesman problem and chinese traveling salesman problem by using chaos neural network modeling
首先分析了旅行商問題在窮舉搜索法下的工作量；其次給出了求解旅行商問題的hopfield神經網路方法，同時分析了利用人工神經網路求解旅行商問題所存在的問題；最後利用混飩神經網路模型求解10城市旅行商問題和中國旅行商問題。 -
Qos routing optimal algorithm in ad hoc networks based on a new hopfield neural network
網路中一種最小功耗路由演算法 -
Our condition and estimate are formulated in terms of the network parameters, the neurons ’ activation functions and the associated equilibrium point. hence, they are easily checkable. it is believed that these results are significant and useful for the design and applications of the delayed hopfield neural networks
這些條件和估計的公式是由網路參數、神經元激活函數以及相應的平衡點構成，所以它們很容易使用，相信這些結果對于帶時間延遲的hopfield神經網路的設計和應用具有一定的重要性和使用價值。 -
The study of the feedback neural network, the analysis of the work principle of hopfield neural network lead to a neural network model with chaotic character
對反饋神經網路進行了研究，在分析現有混沌神經網路的工作原理的基礎上，提出一種新的混沌神經網路模型。 -
Hopfield neural network for eight - queens problem
神經網路求解八皇后問題 -
Recognition research of decayed target based on hopfield neural network
網路的衰變目標識別研究 -
On the asymptotic behavior of hopfield neural network with periodic inputs
型神經網路的全局漸近性質 -
Global asymptotic stability of hopfield neural network system with variable delays and variable coefficients
神經網路系統的全局漸近穩定性的一個充分條件 -
Dual hopfield neural network based model reference adaptive control of ac drive system which has the capability of online parameters tracking
參數在線跟蹤的交流傳動系統雙神經網路模型參考自適應控制 -
Hopfield neural network ( hnn ) algorithm is a typical one in solving this problem, and the early shortcomings of this solution have been greatly improved
Hopfield神經網路演算法是解決這一問題的經典演算法，這一演算法最初具有的不足之處也得到了不斷的改進。 -
In this paper, a general dynamical fuzzy neural network model ? fuzzy hopfield networks with threshold is developed, which is based on the fuzzy operator composition of max ( ) and weakly continuous t - norms. it is shown that the model is global stable with the hamming distance, and its equilibrium point ( attractor ) is lyapunov stable. finally, a simulation example is employed to demonstrate our conclusions
模與取大（ ）模糊運算元的復合，建立了具有一般意義的動態模糊神經網路? ?帶閾值的模糊hopfield神經網路，並系統分析了該動態系統的性能:在hamming距離意義下證明了該網路是穩定的，而且其平衡點（吸引子）具有全局lyapunov穩定性。 -
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。 -
For this reason, theoretical study of neural dynamics has advanced rapidly in recent years. in this dissertation, we investigate the stability, bifurcation and chaotic phenomena of feedback neural networks including hopfield network and cellular neural networks ( cnns )
本文對反饋神經網路（包括hopfield網路及細胞神經網路）的穩定性、極限環以及混沌進行了研究，主要工作概況如下：研究了細胞神經網路（ cnn ）的全局指數穩定性。 -
Chapter 2 different to the stability of the 1 chapter, we studied the stability of ? gain stability. we have known that though the system have lyapnov stability it may be not have ? gain stability. it is necessary to discuss the ? gain stability. chapter 3 we discuss the exponential stability of a new hopfield neural network : bam neural network
第三章，利用dini導數、不等式以及lyapunov函數方法等工具對當今研究的一類熱點神經網路， （ bam ）雙向關聯的神經網路的指數漸近穩定性作了研究，得到了其指數漸近穩定的條件 -
By combining chaotic dynamics and converging dynamics together, the neural network transit gradually to hopfield neural network is made. by introducing converging factor, the aim of controlling chaos is attained, which provides initial value of hopfield neural network that is near to the global optimal solutions, and solve the problem of local minimum. the principle of genetic algorithm is analyzed, and the design and of genetic algorithm are studied
通過把混沌動力學與收斂動力學相結合，使網路逐漸由混沌神經網路向hopfield網路過渡，達到控制混沌的目的，並且提供了一個在全局最優解附近的初值，避開了神經網路權值初始化沒有理論依據的難題，無須確定連接權值和閾值，使神經網路具有物理意義明確、便於與工程應用相結合的特點。
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