Sequential learning for extreme learning machine
Date of Issue2006
School of Electrical and Electronic Engineering
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.
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Nanyang Technological University