神经网络是一个非线性动力学系统,在许多方面都表现出强大的生命力,特别为信息科学界所瞩目.将图形信息输入计算机是CAD、GIS等应用系统中不可避免而又十分繁重的工作,人们一直在追求一种自动化的方法来解决这一问题.该文在深入分析Hopfield模型及多层神经网络的理论基础、学习算法的基础上,尝试使用神经网络的方法进行交叉线的自动识别,提出了一种全新的思路,并且用BP学习算法实现了这一思路.在实验模拟中,该算法显示了优异的性能.

Neural Network is a non-linear dynamics kinetics system, which can do a lot of complex jobs, especially in information science. Inputting image information into computers is an inevitable and troublesome job in many practical systems such as CAD and GIS, etc. An automatic method is needed badly. After analysing fundamental theories of Hopfield model and multi-layered network, a new method to solve the problem realized by a BP algorithm is proposed. During experimental simulations,this algorithm really showed fine performance.