The exponential stability of the delayed cellular neural networks (DCNN's) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new suff...The exponential stability of the delayed cellular neural networks (DCNN's) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Liapunov function. It is shown that the conditions differ from previous ones. The new conditions, which are associated with some initial value, are represented by some blocks of the interconnection matrix.展开更多
Richard Bay Coal Terminal(RBCT)是世界上最大的煤炭码头,该码头将由铁路运进港的煤炭装船出口,1997年出口6.23亿t,在码头内煤炭需要使用85k的带式输送机进行运输,胶带应用的年度预算为210万美元,带式输送机故障引起的非正常停...Richard Bay Coal Terminal(RBCT)是世界上最大的煤炭码头,该码头将由铁路运进港的煤炭装船出口,1997年出口6.23亿t,在码头内煤炭需要使用85k的带式输送机进行运输,胶带应用的年度预算为210万美元,带式输送机故障引起的非正常停机将要付出很大的代价,包括船舶滞留期损失费,堆料机和翻车机的停时损失费等。过去2年,预防性胶带维护使得该公司在这方面获得了很大的优势,由于码头全天候运作,检查带式输送机的工作需要在其运行过程中进行,采取的方法是用高速数字摄像机监视胶带,将从摄像机获得的图像文件进行快速傅里叶转换和微波转换处理,再采用人工神经网络技术进行辨认,以此辅助胶带更换和维护时间安排计划的有关决策,还能在一定程度上追踪一些胶带损伤发生的原因,这些信息用于带式输送机的管理,减少了故障时间,获得了效益。展开更多
基金国家自然科学基金,Technology Research Foundation of Education Ministry of China
文摘The exponential stability of the delayed cellular neural networks (DCNN's) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Liapunov function. It is shown that the conditions differ from previous ones. The new conditions, which are associated with some initial value, are represented by some blocks of the interconnection matrix.
文摘Richard Bay Coal Terminal(RBCT)是世界上最大的煤炭码头,该码头将由铁路运进港的煤炭装船出口,1997年出口6.23亿t,在码头内煤炭需要使用85k的带式输送机进行运输,胶带应用的年度预算为210万美元,带式输送机故障引起的非正常停机将要付出很大的代价,包括船舶滞留期损失费,堆料机和翻车机的停时损失费等。过去2年,预防性胶带维护使得该公司在这方面获得了很大的优势,由于码头全天候运作,检查带式输送机的工作需要在其运行过程中进行,采取的方法是用高速数字摄像机监视胶带,将从摄像机获得的图像文件进行快速傅里叶转换和微波转换处理,再采用人工神经网络技术进行辨认,以此辅助胶带更换和维护时间安排计划的有关决策,还能在一定程度上追踪一些胶带损伤发生的原因,这些信息用于带式输送机的管理,减少了故障时间,获得了效益。