人工脑基于同源同类事物连通本性的模式识别新神经网络模型研究

项目名称： 人工脑基于同源同类事物连通本性的模式识别新神经网络模型研究

项目编号： No.61272077

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 杨国为

作者单位： 南京审计学院

项目金额： 78万元

中文摘要： 人工神经网络是研究人脑认知的科学概念。也是有效的模拟、延伸和扩展人脑模式识别的模型。实际上，模式识别的神经网络模型研究已经取得许多很好的成果，一些模式识别的神经网络模型的正确识别率也达到实用要求。然而，对于一定识别对象，一些传统的模式识别模型遇到了模式识别正确识别率很难再提高的瓶颈，本项目通过对同源同类事物连通本性的认知，采用申请人提出的人工脑信息处理方法、创新的智能计算方法和改进的函数极值计算方法研究基于同源同类事物连通本性的人脑模式识别的模拟、延伸和扩展等问题，拟提出并深入研究几类人工脑基于同源同类事物连通本性的模式识别新神经网络模型{神经元（计算式）、网络拓扑结构（神经元连接方式，连接权值取值）、网络算法（保同源同类事物局部直接连通的结构学习算法、工作算法）}。 项目的预期成果有望丰富和发展对人脑模式识别的认知研究，突破一些传统模式识别模型遇到的正确识别率很难再提高的瓶颈。

中文关键词： 人工脑；模式识别；人工神经网络；特征提取；人脸识别

英文摘要： Artificial neural network is a scientific concept for the investigation of cognition of human brain as well as a effective model to mimic,extend, and expand pattern recognition of human brain. In practice, a number of remarkable outcomes on neural network model using pattern recognition have already been available, and also the accurate recognition rate of some neural network models have met the practical requirement. However, some conventional pattern recognition models face the bottleneck that the accurate rate of pattern recognition for some particular recognition objects can be hardly improved. According to the congition of connectivity nature of objects within the same source and same category, in this project several issues with regard to mimicing,extending, and expanding the pattern recognition of connectivity nature of human brain within the same source and same category will be researched using an artificial brain information processing method, a creative intelligent computing method, and an improved function extremum computing method, proposed by applicants. In addition, some new neural network models using pattern recognition of artificial brain based on connectivity nature within the same source and same category, which consists of neutron with formulas, network topology with connecting way between n

英文关键词： Artificial Brain；Pattern Recognition；Artificial Neural Networks；feature extraction；Face recognition