Memory Retrieval in the B-Matrix Neural Network

TL;DR

This paper enhances the memory retrieval process in B-Matrix neural networks by applying delta learning to improve the accuracy and efficiency of recalling stored memories.

Contribution

It introduces delta learning into the B-Matrix memory retrieval method to increase retrieval success rates.

Findings

Improved memory retrieval accuracy

Faster convergence in memory recall

Enhanced robustness to incomplete fragments

Abstract

This paper is an extension to the memory retrieval procedure of the B-Matrix approach [6],[17] to neural network learning. The B-Matrix is a part of the interconnection matrix generated from the Hebbian neural network, and in memory retrieval, the B-matrix is clamped with a small fragment of the memory. The fragment gradually enlarges by means of feedback, until the entire vector is obtained. In this paper, we propose the use of delta learning to enhance the retrieval rate of the stored memories.