Hopfield神经网络(Hopfield Neural Network,简称 HNN),是美国加州理工学院物理学家Hopfield教授1982年提出的一种反馈型神经网络,信号不但能向前,还能向后传递(输出信号又反馈回来变成输入信号。而前面所介绍的BP网络是一种前馈网络,信号只能向前传递)。他在Hopfield神经网络中引入了“能量函数”概念,使网络...
The algorithm is based on the geometric theory of differential equations and is implemented by a Hopfield neural network (HNN) . In the paper we first introduce the phases of estimation and interpretation, then their interaction and cooperation is presented. Finally some results are shown....
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By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in...
In the last chapter, we saw how a generalized delta rule (backwards error propagation) network could slowly learn to recognize a series of patterns. The delta rule network adapted slowly while training repetitively on a set of examples (sometimes a set of training examples passes through the ...
In various scheduling applications, the Hopfield Neural Network is commonly applied to obtain an optimal solution [48], [50]. A competitive learning rule reduces the network complexity and provides a highly effective means of obtaining this optimal solution. This new technique is called the Competiti...