Orthonormal Basis Latice Neural Networks

Category:

Description

Lattice based neural networks are capable of resolving some difficult non-linear problems and have been successfully employed to solve real-world problems. In this paper a novel model of a lattice neural network (LNN) is presented. This new model generalizes the standard basis lattice neural network (SB-LNN) based on dendritic computing. In particular, we show how each neural dendrite can work on a different orthonormal basis than the other dendrites. We present experimental results that demonstrate superior learning performance of the new Orthonormal Basis Lattice Neural Network (OB-LNN) over SB-LNNs.

Additional information

Author

Barmpoutis, A., Ritter, G. X.

Journal

In Computational Intelligence Based on LatticeTheory, V. Kaburlasos and G. X. Ritter (ed.)

Publisher

Springer-Verlag, Heidelberg, Germany

Year

2007

Pages

43-56

DOI

https://doi.org/10.1007/978-3-540-72687-6_3

Citation

Citation

Barmpoutis, A. and Ritter, G., 2007. Orthonormal Basis Latice Neural Networks. In Computational Intelligence Based on LatticeTheory, V. Kaburlasos and G. X. Ritter (ed.), pp. 43-56. https://doi.org/10.1007/978-3-540-72687-6_3

BibTex

@article{digitalWorlds:173,
doi = {https://doi.org/10.1007/978-3-540-72687-6_3},
author = {Barmpoutis, A. and Ritter, G. X.},
title = {Orthonormal Basis Latice Neural Networks},
journal = {In Computational Intelligence Based on LatticeTheory, V. Kaburlasos and G. X. Ritter (ed.)},
year = {2007},
pages = {43-56}
}