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Partitioned online sequential extreme learning machine for large ordered system modeling
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DOI：10.1016/j.neucom.2011.12.049.png)
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In this paper, we propose an algorithm entitled partitioned OS-ELM (P05-ELM) that partitions a large data matrix into small matrices, applies an RLS (Recursive Least Square) scheme in each of the small sub-matrices and assembles the whole estimation vector by the concatenation of the sub-vectors from the RLS outputs of the sub-matrices. Consequently, the algorithm is less complex than the conventional OS-ELM and maintains an almost compatible estimation performance. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Extreme learning machine
OS-ELM
RLS
Partitioning
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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