Resilient back-propagation Neural Network for approximation Weighted Geometric Dilution of Precision

Chien Sheng Chen, Szu-Lin Su, He Nian Shou, Wen Hsiung Liu

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

The conventional matrix inversion method for weighted geometric dilution of precision (WGDOP) calculation has a large amount of operation. This paper employs an artificial neural network approach, namely, the resilient back-propagation (Rprop) method to implement WGDOP. We also present two novel architectures to implement the Rprop-based WGDOP. Simulation results show that the proposed architectures always yield superior estimation accuracy with much reduced computational complexity, compared to conventional implementation methods for WGDOP. The proposed architectures are applicable not only to global positioning system (GPS) but also to wireless sensor networks (WSN) and cellular communication systems regardless of the number of the measurement units. To further reduce the complexity, we propose to combine the serving base station (BS) and the optimal three measurements with minimum WGDOP to reduce the number of subsets in cellular communication systems.

原文English
主出版物標題Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
頁面53-58
頁數6
DOIs
出版狀態Published - 2010 十一月 1
事件2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010 - Chengdu, China
持續時間: 2010 七月 92010 七月 11

出版系列

名字Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
7

Other

Other2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
國家China
城市Chengdu
期間10-07-0910-07-11

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

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  • 引用此

    Chen, C. S., Su, S-L., Shou, H. N., & Liu, W. H. (2010). Resilient back-propagation Neural Network for approximation Weighted Geometric Dilution of Precision. 於 Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010 (頁 53-58). [5563546] (Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010; 卷 7). https://doi.org/10.1109/ICCSIT.2010.5563546