Analysis of Pattern Recognition Algorithms using Associative Memory Approach: A Comparative Study between the Hopfield Network and Distributed Hierarchical Graph Neuron (DHGN)

被引：3

作者：

Amin, A. H. Muhamad ^{[1
]}

Mahmood, R. A. Raja ^{[1
]}

Khan, A. I. ^{[1
]}

机构：

[1] Monash Univ, Clayton Sch IT, Clayton, Vic 3168, Australia

来源：

8TH IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY WORKSHOPS: CIT WORKSHOPS 2008, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/CIT.2008.Workshops.65

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we conduct a comparative analysis of two associative memory-based pattern recognition algorithms. We compare the established Hopfield network algorithm with our novel Distributed Hierarchical Graph Neuron (DHGN) algorithm. The computational complexity and recall efficiency aspects of these algorithms are discussed. The results show that DHGN offers lower computational complexity with better recall efficiency compared to the Hopfield network.

引用

页码：153 / 158

页数：6

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