PSO-based cloning template design for CNN associative memories

Authors:
A. Giaquinto;G. Fornarelli
Affiliations:
Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Bari, Italy;Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Bari, Italy
Venue:
IEEE Transactions on Neural Networks
Year:
2009

Citing 5
Cited 0

Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
Designing Templates for Cellular Neural Networks Using Particle Swarm Optimization

AIPR '04 Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop
Particle Swarm Optimization for Image Noise Cancellation

ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1
Cellular Neural Networks and Visual Computing

Cellular Neural Networks and Visual Computing
An Improved Particle Swarm Optimization for Evolving Feedforward Artificial Neural Networks

Neural Processing Letters

Quantified Score

Hi-index	0.05

Visualization

Abstract

In this brief, a synthesis procedure for cellular neural networks (CNNs) with space-invariant cloning templates is proposed. The design algorithm is based on the use of the evolutionary algorithm of the particle swarm optimization (PSO) with the application to associative memories. The proposed synthesis procedure takes into account requirements in terms of robustness to parametric variations. Numerical results show that the networks also guarantee good performances in terms of correct recall in the presence of noisy patterns.