IDENTIFICATION OF DISTRIBUTED PARAMETER SYSTEMS BASED ON MULTIVARIABLE ESTIMATION AND WIRELESS SENSOR NETWORKS

2008 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Distributed Parameter Systems ◽  
Wireless Sensor ◽  
Distributed Parameter

scholarly journals Memory Distributed LMS for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Fangmin Xu ◽  
Chenyang Zheng ◽  
Haiyan Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cost Function ◽  
Lms Algorithm ◽  
Wireless Sensor ◽  
Distributed Parameter ◽  
Mean Square ◽  
Central Processing ◽  
The Cost ◽  
Local Results

Due to the limited communication resource and power, it is usually infeasible for sensor networks to gather data to a central processing node. Distributed algorithms are an efficient way to resolve this problem. In the algorithms, each sensor node deals with its own input data and transmits the local results to its neighbors. Each node fuses the information from neighbors and its own to get the final results. Different from the existing work, in this paper, we present an approach for distributed parameter estimation in wireless sensor networks based on the use of memory. The proposed approach consists of modifying the cost function by adding extra statistical information. A distributed least-mean squares (d-LMS) algorithm, called memory d-LMS, is then derived based on the cost function and analyzed. The theoretical performances of mean and mean square are analyzed. Moreover, simulation results show that the proposed algorithm outperforms the traditional d-LMS algorithm in terms of convergence rate and mean square error (MSE) performance.

Principles of Wireless Sensor Networks

2012 ◽  
Author(s):  
Mohammad S. Obaidat ◽  
Sudip Misra
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor
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