迭代学习控制
通信源
计算机科学
解码方法
编码(内存)
迭代和增量开发
网络拓扑
迭代法
跟踪(教育)
过程(计算)
区间(图论)
理论计算机科学
算法
人工智能
数学
电信
计算机网络
控制(管理)
组合数学
软件工程
操作系统
教育学
心理学
作者
Wenjun Xiong,Xinghuo Yu,Yao Chen,Jie Gao
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2017-06-01
卷期号:28 (6): 1473-1480
被引量:54
标识
DOI:10.1109/tnnls.2016.2532351
摘要
This brief investigates the quantized iterative learning problem for digital networks with time-varying topologies. The information is first encoded as symbolic data and then transmitted. After the data are received, a decoder is used by the receiver to get an estimate of the sender's state. Iterative learning quantized communication is considered in the process of encoding and decoding. A sufficient condition is then presented to achieve the consensus tracking problem in a finite interval using the quantized iterative learning controllers. Finally, simulation results are given to illustrate the usefulness of the developed criterion.
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