articleIEEE Transactions on Neural NetworksNov 1, 2006Closed access

A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks

NLNanying LiangGHGuang-Bin HuangPSP. SaratchandranNSN. Sundararajan

Nanyang Technological University

PubMed
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Abstract

In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact…

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Topics & keywords

Topics
Keywords
  • Extreme learning machine
  • Computer science
  • Benchmark (surveying)
  • Generalization
  • Algorithm
  • Feedforward neural network
  • Feed forward
  • Piecewise
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