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...

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主要作者: Liang, Nanying
其他作者: Paramasivan Saratchandran
格式: Theses and Dissertations
出版: 2008
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在線閱讀:https://hdl.handle.net/10356/4601
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總結: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.