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 Proceedings of FUZZ06: International Conference on Fuzzy Systems

Year

2006

Month

July 16-21

Pages

331-336

DOI

https://doi.org/10.1109/FUZZY.2006.1681733

Citation

Citation

Barmpoutis, A. and Ritter, G., 2006. Orthonormal Basis Latice Neural Networks. In Proceedings of FUZZ06: International Conference on Fuzzy Systems, pp. 331-336. https://doi.org/10.1109/FUZZY.2006.1681733

BibTex

@article{digitalWorlds:175,
doi = {https://doi.org/10.1109/FUZZY.2006.1681733},
author = {Barmpoutis, A. and Ritter, G. X.},
title = {Orthonormal Basis Latice Neural Networks},
journal = {In Proceedings of FUZZ06: International Conference on Fuzzy Systems},
month = {July 16-21},
year = {2006},
pages = {331-336}
}