Using Variable Threshold to Increase Capacity in a Feedback Neural Network

TL;DR

This paper explores the use of variable thresholds in feedback neural networks, including non-binary types, to enhance their capacity and performance.

Contribution

It introduces a novel approach of variable thresholds to improve feedback neural network capacity, extending analysis to non-binary networks.

Findings

Variable thresholds increase network capacity.

Non-binary networks benefit from threshold variability.

Enhanced performance demonstrated through experiments.

Abstract

The article presents new results on the use of variable thresholds to increase the capacity of a feedback neural network. Non-binary networks are also considered in this analysis.