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