改进的模糊神经网络算法在车型识别中的应用  

Improved Application of Fuzzy Neural Network in Vehicle Model Recognition

作　　者：杨平乐[1] 王勇[1] 张勤阁[2] 

机构地区：[1]江苏科技大学张家港校区基础部计算机教研室,张家港215000 [2]中国矿业大学理学院,徐州221116

出　　处：《世界科技研究与发展》2009年第5期814-816,857,共4页World Sci-Tech R&D

摘　　要：FBP和FCNN网络是模式识别中应用最为广泛的两种神经网络,本文将这两种网络应用于车型识别,分别建立了车型识别模型。利用混沌对初值的极端敏感依赖提出了FCNN网络算法,通过对车型图像数据库进行仿真实验,对比分析它们各自的识别率和泛化能力等性能指标,证明了FCNN网络算法的有效性。FBP and FCNN neural networks are widely applied in pattern recognition. These two methods are used for vehicle model recogni- tion, and their face recognition models are established respectively. Basd on analyzing the theory of fuzzy neural network recognition, simulation experiments are carried out using vehicle model recognition database. The characteristics of two neural networks, such as recognition rate and generalization ability are discussed, which should be considered in the practical applications of these two types of neural networks. Finally we prove FCNN neural networks are effective.

关 键 词：FBP神经网络 FCNN神经网络 车型识别 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]