A survey of the past, present and future of echo state networks
- DOI
- 10.2991/eeeis-16.2017.105How to use a DOI?
- Keywords
- Echo State Network; Prediction; Structure Improvement; Modelling capability analysis
- Abstract
Along with the development of Machine Learning, statistic and Artificial Intelligence, people are exposed to myriad of big data. Meanwhile, accurate data analysis is difficult. Echo state network (ESN) algorithms are widely researched and applied in many fields. Owing to their potential for exact prediction and simple training process, scientists pay more attention to the research of ESN. In this paper, the representative research is carried out to sum up the research achievements on ESN, and the future development direction is discussed by pointing out the key technical challenges and we suggest several strategies for tackling the challenges.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Guan-Fang Wu AU - Hong-Yan Cui PY - 2016/12 DA - 2016/12 TI - A survey of the past, present and future of echo state networks BT - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016) PB - Atlantis Press SP - 850 EP - 861 SN - 2352-5401 UR - https://doi.org/10.2991/eeeis-16.2017.105 DO - 10.2991/eeeis-16.2017.105 ID - Wu2016/12 ER -