Event-triggered state estimation for Markovian jumping neural networks: On mode-dependent delays and uncertain transition probabilities

This paper is concerned with the event-triggered state estimation (ETSE) problem for a class of discrete-time Markovian jumping neural networks mode-dependent time-delays and uncertain transition probabilities. The parameters experience switches that are characterized by chain whose probabilities allowed to be uncertain. mechanism introduced in sensor-to-estimator channel reduce frequency signal communication. aim this develop an ETSE scheme such error dynamics exponentially ultimately bounded mean square. To achieve aim, two sufficient conditions proposed first one guaranteeing existence required estimator, second giving algorithm designing corresponding estimator gain solving some matrix inequalities. In end, validity illustrated numerical example.