A morphological associative memory employing a reverse recall

Authors:
Hidetaka Harada;Tsutomu Miki
Affiliations:
Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan;Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Year:
2010

Citing 4
Cited 0

Bidirectional associative memories

IEEE Transactions on Systems, Man and Cybernetics
Morphological bidirectional associative memories

Neural Networks
Improvement of the perfect recall rate of block splitting type morphological associative memory using a majority logic approach

ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Morphological associative memories

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recently the morphological associative memory proposed by Ritter attracts researcher's attention. The model is superior to other models in terms of memory capacity and perfect recall rate. However the conventional MAM has a problem that the correct pattern cannot be recalled if a pattern has inclusive relation to other stored pattern. In this paper, as one of the solutions, an effective MAM employing a reverse recall is proposed. In the proposed method, candidate patterns of an input can be estimated by reverse recall from the kernel image recalled by a given inclusion input pattern, and then the plausible recall pattern can be determined by comparing the candidates with input pattern. We confirm the validity of the proposed method through hetero association experiments for twenty six alphabet patterns with inclusion patterns.