Robust recursive complex extreme learning machine algorithm for finite numerical precision

Authors:
Junseok Lim;Koeng Mo Sung;Joonil Song
Affiliations:
Dept. of Electronics Engineering, Sejong University, Seoul, Korea;School of Electrical Engineering, Seoul National University, Seoul, Korea;Samsung Electronics Co., Ltd
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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Abstract

Recently, a new learning algorithm for single-hidden-layer feedforward neural network (SLFN) named the complex extreme learning machine (C-ELM) has been proposed in [1]. In this paper, we propose a numerically robust recursive least square type C-ELM algorithm. The proposed algorithm improves the performance of C-ELM especially in finite numerical precision. The computer simulation results in the various precision cases show the proposed algorithm improves the numerical robustness of C-ELM.