Bill Money Classification for Intelligent OA Systems Using Evolutional Neural Networks

在本课题中，我们提出了一种基于进化机制的神经网络实现票据货币智能模式分类的新方法，以实现办公自动化。本课题是综合一个智能模式分类系统。为了完成项目研究，我们采用了以下方法来综合这些智能控制系统：(1)神经网络的学习能力我们利用通信信道的信息度量来制定神经网络的学习能力。(2)遗传算法进化机制的出现为了提高所考虑的神经网络的学习能力(1)，我们引入了遗传算法，并找到了学习曲线的全局最小值。为了实现智能，我们不仅使用数值数据，还使用图像信息处理作为多媒体数据处理。(4)神经分类器的硬件实现为了加快分类速度，降低分类成本，我们实现了票据货币分类的神经硬件。

In this project, we have proposed a new approach to realize the intelligent pattern classification of bill money to enforce the office automation based on neural networks with evolution mechanism. The present project is to synthesize an intelligent pattern classifier system. To complete the project study, we have adopted the following approach to synthesize these intelligent control systems :(1) Learning Ability of the Neural networkWe have formulated the learning ability of neural networks by using information measure of the communication channel.(2) Emergence of Evolution Mechanism by Genetic AlgorithmsTo improve the learning ability of neural networks considered (1), we have introduced the genetic algorithms and find the global minimum of the learning curves.(3) Construction of Image Understanding by Neural NetworksTo realize the intelligence we have used not only numerical data but also image information processing as a multi-media data processing.(4) Hardware Implementation of Neuro-ClassifierIn order to speed up the classification and make the cost lower, we have implemented the neuro- hardware for bill money classification.