Researchers’ Work from Hangzhou Normal University Focuses on Neural Networks and Learning Systems (Simultaneous State and Unknown Input Estimation for Complex Networks With Redundant Channels Under Dynamic Event-triggered Mechanisms)

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 originating from Hangzhou, People’s Republic of China, by NewsRx correspondents, research stated, “This article addresses the simultaneous state and unknown input estimation problem for a class of discrete time-varying complex networks (CNs) under redundant channels and dynamic event-triggered mechanisms (ETMs). The redundant channels, modeled by an array of mutually independent Bernoulli distributed stochastic variables, are exploited to enhance transmission reliability.”