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

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3 Author(s)
Amin, A.H.M. ; Clayton Sch. of IT, Monash Univ., Clayton, VIC ; Mahmood, R. ; Khan, A.I.

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.

Published in:

Computer and Information Technology Workshops, 2008. CIT Workshops 2008. IEEE 8th International Conference on

Date of Conference:

8-11 July 2008