Article ID Journal Published Year Pages File Type
406811 Neurocomputing 2013 11 Pages PDF
Abstract

The heteroassociative morphological memories (HMMs) are one kind of morphological associative memories (MAMs). Although they have many advantages, there is a serious shortcoming: HMMs are incomplete, that is, they cannot give a guarantee of perfect recall memories, even though without any input noises. This problem has become a bottleneck in the development and applications of HMMs, and also one of difficult subjects in this field. Aiming at the problem, this paper presents a new method of HMMs, called four-dimensional stored HMMs (FDSHMMs). It includes three work stages: pretreatment, memory, and recall. Both computational method and experimental method show that FDSHMMs can significantly improve the HMMs. They can guarantee perfect recall memories for perfect inputs or within a certain noise range, just like the auto-associative morphological memories (AMMs) can do. FDSHMMs remove the bottleneck of HMMs and bring us a bright prospect of applications.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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