Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Smart Structures and Systems Volume 19, Number 4, April 2017 , pages 383-391 DOI: https://doi.org/10.12989/sss.2017.19.4.383 |
|
|
|
Distributed estimation over complex adaptive networks with noisy links |
||
Morteza Farhid, Mohammad H. Sedaaghi and Mousa Shamsi
|
||
| Abstract | ||
| In this paper, we investigate the impacts of network topology on the performance of a distributed estimation algorithm, namely combine- then-adaptive (CTA) diffusion LMS, based on the data with or without the assumptions of temporal and spatial independence with noisy links. The study covers different network models, including the regular, small-world, random and scale-free whose the performance is analyzed according to the mean stability, mean-square errors, communication cost (link density) and robustness. Simulation results show that the noisy links do not cause divergence in the networks. Also, among the networks, the scale free network (heterogeneous) has the best performance in the steady state of the mean square deviation (MSD) while the regular is the worst case. The robustness of the networks against the issues like node failure and noisier node conditions is discussed as well as providing some guidelines on the design of a network in real condition such that the qualities of estimations are optimized. | ||
| Key Words | ||
| complex networks; adaptive networks; diffusion mode; distributed estimation; LMS algorithm | ||
| Address | ||
| Department of Electrical Engineering, Sahand university of technology, Tabriz, Iran | ||