Exponential state estimation for delayed recurrent neural networks with sampled-data

2011 ◽  
Vol 69 (1-2) ◽  
pp. 555-564 ◽  
Author(s):  
Nan Li ◽  
Jiawen Hu ◽  
Jiming Hu ◽  
Lin Li
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Recurrent Neural Networks ◽  
Sampled Data

scholarly journals Event-Triggered State Estimation for a Class of Delayed Recurrent Neural Networks with Sampled-Data Information

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Hongjie Li
Keyword(s):  
Neural Networks ◽  
Dynamic System ◽  
State Estimation ◽  
Recurrent Neural Networks ◽  
Linear Matrix ◽  
Time Varying ◽  
Sampled Data ◽  
Information Communication ◽  
State Estimator ◽  
Event Triggered

The paper investigates the state estimation problem for a class of recurrent neural networks with sampled-data information and time-varying delays. The main purpose is to estimate the neuron states through output sampled measurement; a novel event-triggered scheme is proposed, which can lead to a significant reduction of the information communication burden in the network; the feature of this scheme is that whether or not the sampled data should be transmitted is determined by the current sampled data and the error between the current sampled data and the latest transmitted data. By using a delayed-input approach, the error dynamic system is equivalent to a dynamic system with two different time-varying delays. Based on the Lyapunov-krasovskii functional approach, a state estimator of the considered neural networks can be achieved by solving some linear matrix inequalities, which can be easily facilitated by using the standard numerical software. Finally, a numerical example is provided to show the effectiveness of the proposed event-triggered scheme.

scholarly journals Extended dissipativity and non-fragile synchronization for Recurrent neural networks with multiple time-varying delays via sampled-data control

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
R. Anbuvithya ◽  
S. Dheepika Sri ◽  
R. Vadivel ◽  
Nallappan Gunasekaran ◽  
P. Hammachukiattikul
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Multiple Time ◽  
Time Varying ◽  
Sampled Data ◽  
Data Control ◽  
Sampled Data Control

State Estimation and Tracking Problems: A Comparison Between Kalman Filter and Recurrent Neural Networks

2004 ◽  
pp. 275-281 ◽  
Author(s):  
S. Kumar Chenna ◽  
Yogesh Kr. Jain ◽  
Himanshu Kapoor ◽  
Raju S. Bapi ◽  
N. Yadaiah ◽  
...  
Keyword(s):  
Neural Networks ◽  
Kalman Filter ◽  
State Estimation ◽  
Recurrent Neural Networks

H∞ State Estimation of Memristor-based Recurrent Neural Networks with Mixed Delay

2019 ◽  
Author(s):  
Xiangxiang Wang ◽  
Yongbin Yu ◽  
Nijing Yang ◽  
Haowen Tang ◽  
Shouming Zhong ◽  
...  
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Recurrent Neural Networks ◽  
Mixed Delay

scholarly journals Sampled-data state estimation for neural networks of neutral type

2014 ◽  
Vol 2014 (1) ◽  
Author(s):  
Changchun Yang ◽  
Yongqing Yang ◽  
Manfeng Hu ◽  
Xianyun Xu
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Neutral Type ◽  
Sampled Data
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