Adaptive neural nets filter using a recursive Levenberg-Marquardt search direction

  title={Adaptive neural nets filter using a recursive Levenberg-Marquardt search direction},
  author={L.S.H. Ngia and Johan Sjoberg and Mats Viberg},
  journal={Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)},
  pages={697-701 vol.1}
This paper proposes a recursive Levenberg-Marquardt (LM) search direction as the training algorithm for non-linear adaptive filters, which use multi-layer feed forward neural nets as the filter structures. The neural nets can be considered as a class of non-linear adaptive filters with transversal or recursive filter structures. In the off-line training, the LM method is regarded as an intermediate method between the steepest descent (SD) and Gauss-Newton (GN) methods, and it has better… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 10 references

Theory and Practice of Recursive Identification

  • L. Ljung, T. Söderström
  • 1983
Highly Influential
5 Excerpts

Linearized least-squares training of multilayer feedforward neural networks

  • S. C. Douglas, T. H. Meng
  • In Int. Joint Conf. of Neural Networks,
  • 1991
2 Excerpts

An adaptive least squares algorithm for the efficient training of artificial neural networks

  • S. Kollias, D. Anastassiou
  • IEEE Trans. on Circuits and Systems,
  • 1989
1 Excerpt

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