Learning in Competitive Network with Haeusslers Equation adapted using FIREFLY algorithm
Neural and Evolutionary Computing
2019-07-10 v1 Computer Vision and Pattern Recognition
Abstract
Many of the competitive neural network consists of spatially arranged neurons. The weigh matrix that connects cells represents local excitation and long-range inhibition. They are known as soft-winner-take-all networks and shown to exhibit desirable information-processing. The local excitatory connections are many times predefined hand-wired based depending on spatial arrangement which is chosen using the previous knowledge of data. Here we present learning in recurrent network through Haeusslers equation and modified wiring scheme based on biologically based Firefly algorithm. Following results show learning in such network from input patterns without hand-wiring with fixed topology.
Keywords
Cite
@article{arxiv.1907.04160,
title = {Learning in Competitive Network with Haeusslers Equation adapted using FIREFLY algorithm},
author = {N. Joshi},
journal= {arXiv preprint arXiv:1907.04160},
year = {2019}
}