Recent Research from School of Automation Highlight Findings in Neural Networks and Learning Systems (A Comparative Study of Deep Neural Network-aided Canonical Correlation Analysis-based Process Monitoring and Fault Detection Methods)

摘要

By a News Reporter-Staff News Editor at Network Daily News – Investigators publish new report on Networks - Neural Networks and Learning Systems. According to news reporting originating from Changsha, People’s Republic of China, by NewsRx correspondents, research stated, “Multivariate analysis is an important kind of method in process monitoring and fault detection, in which the canonical correlation analysis (CCA) makes use of the correlation change between two groups of variables to distinguish the system status and has been greatly studied and applied. For the monitoring of nonlinear dynamic systems, the deep neural network-aided CCA (DNN-CCA) has received much attention recently, but it lacks a general definition and comparative study of different network structures.”