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:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	https://hdl.handle.net/10356/4601
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Institution:	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

Sequential learning for extreme learning machine

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