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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Bibliographic Details
Main Author: Liang, Nanying
Other Authors: Paramasivan Saratchandran
Format: Theses and Dissertations
Published: 2008
Subjects:
Online Access:https://hdl.handle.net/10356/4601
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Institution: Nanyang Technological University
Description
Summary: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.