本论文揭示，作为两种并行的神经计算模型，BP和Hopfield类型神经网络都可以有效地对二次型V（x）=T/2+TVxxPxqx实现最小化求解。而且，尽管BP和Hopfield类型神经网络在网络设计思想和网络结构上呈现出很大的差异，但是它们在二次型函数最小化问题上都表现出了相同的学习能力，这说明两者具有本质的联系。

A quadratic performance index is investigated for the online neural remedy for drift phenomenon of redundant robot manipulators. Computer simulations performed based on a three-link planar robot arm show the efficacy of such a quadratic-index based neural-remedy scheme.

本文介绍了国际互联网WWW和其最新核心技术之一的Java语言的现状和发展，提出了一种将JavaApplet与WWW有机结合起来的客户在线交谈系统的方案，并结合具体情况讲述该交互系统在Internet（尤其是WWW）中的改进与多方面应用。

In this Letter, by following Zhang et al. is method, a recurrent neural network (termed as Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying convex quadraticprogramming problem subject to time-varying linear-equality constraints. Different from conventional gradient-based neural networks (GNN), such a ZNN model makes full use of the time-derivative information of time-varying coefficient. The resultant ZNN model is theoretically proved to have global exponential convergence to the time-varying theoretical optimal solution of the investigated time-varying convex quadratic program. Computer-simulation results further substantiate the effectiveness, efficiency and novelty of such ZNN model and method.

A recurrent neural network called the dual neural network is proposed in this Letter for solving the strictly convex quadratic programming problems. Compared to other recurrent neural networks, the proposed dual network with fewer neurons can solve quadratic programming problems subject to equality, inequality, and bound constraints. The dual neural network is shown to be globally exponentially convergent to optimal solutions of quadratic programming problems. In addition, compared to neural networks containing high-order nonlinear terms, the dynamic equation of the proposed dual neural network is piecewise linear, and the network architecture is thus much simpler. The global convergence behavior of the dual neural network is demonstrated by an illustrative numerical example. Ù 2002 Elsevier Science B.V. All rights reserved.