An Efficient Algorithm for the Incremental Broad Learning System by Inverse Cholesky Factorization of a Partitioned Matrix

An Efficient Algorithm for the Incremental Broad Learning System by Inverse Cholesky Factorization of a Partitioned Matrix

In this paper, we propose an efficient algorithm to accelerate the existing Broad Learning System (BLS) algorithm for new added nodes. The existing BLS algorithm computes the output weights from the pseudoinverse with the ridge regression approximation, and updates the pseudoinverse iteratively. As...

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Bibliographic Details
Main Authors: Hufei Zhu, Zhulin Liu, C. L. Philip Chen, Yanyang Liang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Broad learning system (BLS)
incremental learning
added nodes
random vector functional-link neural networks (RVFLNN)
single layer feedforward neural networks (SLFN)
efficient algorithms
Online Access:https://ieeexplore.ieee.org/document/9326429/

Internet

https://ieeexplore.ieee.org/document/9326429/

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