Sequential learning for extreme learning machine
A novel sequential learning algorihtm for training Single Hidden Layer Feedforward Neural Network (SLFN), Online Sequential Extreme Learning Machine (OS-ELM) is proposed. OS-ELM is based on the combination of Extreme Learning Machine (ELM) and the recursive least-squares (RLS) algorithm. In the thes...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Theses and Dissertations |
| 出版: |
2008
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/4601 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Nanyang Technological University |
| id |
sg-ntu-dr.10356-4601 |
|---|---|
| record_format |
dspace |
| spelling |
sg-ntu-dr.10356-46012023-07-04T17:38:57Z Sequential learning for extreme learning machine Liang, Nanying Paramasivan Saratchandran School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems A novel sequential learning algorihtm for training Single Hidden Layer Feedforward Neural Network (SLFN), Online Sequential Extreme Learning Machine (OS-ELM) is proposed. OS-ELM is based on the combination of Extreme Learning Machine (ELM) and the recursive least-squares (RLS) algorithm. In the thesis, we explore the theory and the implementation of the proposed algorithm. Further the performance of the algorithm is evaluated on various application from the areas of regression, classification, and time seriese prediction. DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T09:55:06Z 2008-09-17T09:55:06Z 2006 2006 Thesis Liang, N. (2006). Sequential learning for extreme learning machine. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/4601 10.32657/10356/4601 Nanyang Technological University application/pdf |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
| collection |
DR-NTU |
| topic |
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems |
| spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Liang, Nanying Sequential learning for extreme learning machine |
| description |
A novel sequential learning algorihtm for training Single Hidden Layer Feedforward Neural Network (SLFN), Online Sequential Extreme Learning Machine (OS-ELM) is proposed. OS-ELM is based on the combination of Extreme Learning Machine (ELM) and the recursive least-squares (RLS) algorithm. In the thesis, we explore the theory and the implementation of the proposed algorithm. Further the performance of the algorithm is evaluated on various application from the areas of regression, classification, and time seriese prediction. |
| author2 |
Paramasivan Saratchandran |
| author_facet |
Paramasivan Saratchandran Liang, Nanying |
| format |
Theses and Dissertations |
| author |
Liang, Nanying |
| author_sort |
Liang, Nanying |
| title |
Sequential learning for extreme learning machine |
| title_short |
Sequential learning for extreme learning machine |
| title_full |
Sequential learning for extreme learning machine |
| title_fullStr |
Sequential learning for extreme learning machine |
| title_full_unstemmed |
Sequential learning for extreme learning machine |
| title_sort |
sequential learning for extreme learning machine |
| publishDate |
2008 |
| url |
https://hdl.handle.net/10356/4601 |
| _version_ |
1772828672448790528 |