In this paper, we discuss a method for analyzing the energy function of a Hopfield鈥恡ype neural network. In order to analyze the energy function which solves the given minimization problem, or simply, the problem, we define the standard form of the energy function. In general, a ...
1.In the present research,the authors converted restricted networks of combinational circuits into energy functions with discrete Hopfield neural network models, used ptimization algorithm to obtain minimum of energy functions,the test vectors of stuck faults and found fault coverage is 100 percent.介绍...
We describe an approach to optimization based on a multiple-restart quasi-Hopfield network where the only problem-specific knowledge is embedded in the energy function that the algorithm tries to minimize. We apply this method to three different variants of the graph coloring problem: the minimum ...
This paper presented chaotic neural network of simulated annealing(ACNN)method based on improved energy function for the shortage that the conventional Hopfield neural networks(HNN) tended to be trapped into local minima.Controled HNN with chaos mechanism and chaos dynamics by annealing strategy,therefor...
A complex phase-conjugate neural network model with a Hopfield-like energy function has been proposed, and a physical interpretation is given to its dynami... Mitsuo,Takeda,Takaaki,... - 《Journal of the Optical Society of America A》 被引量: 58发表: 1992年 Evolution and stability of pulse...
(26) 0 For the choice of a Heaviside firing rate function f(u) = H(u − h) this reduces to E[u] = − 1 � 2...French D A 2004 Identification of a free energy functional in an integro-differential equation model for neuronal network activity Appl. Math. Lett. 17 1047-51...
A simple visualization of energy function and energy gap in hopfield nets 好文要顶 关注我 收藏该文 微信分享 Jiang, X. 粉丝- 26 关注- 3 +加关注 0 0 升级成为会员 « 上一篇: android:layout_weight » 下一篇: Difference between Satisfiable, Valid, Unsatisfiable & Invalid ...
making decisions based on thresholds and weights. By adopting the loss minimization and gradient descent, training could yield a linear plane for classification. However, it was proven that the Perceptron was limited to linear problems. In 1982, John J. Hopfield designed the Hopfield Network [32]...
In this paper, we present an neural network approach to solve a set of nonlinear equations. A modified Hopfield network has been developed to optimize a energy function. This approach provides faster convergence and extremely accurate so... D Mishra,PK Kalra - 《Engineering Letters》 被引量: ...
We discuss systemati... 关键词: Convergence Neural networks Neurons Hysteresis Hopfield neural networks Cost function Traveling salesman problems Computer networks Mathematics Australia DOI: 10.1109/72.557700 年份: 1997 收藏 引用 批量引用 报错 分享 全部来源 免费下载 求助全文 国家科技图书文献中心 (...