Title :
Analysis of Pattern Recognition Algorithms Using Associative Memory Approach: A Comparative Study between the Hopfield Network and Distributed Hierarchical Graph Neuron (DHGN)
Author :
Amin, A. H Muhamad ; Mahmood, R. A Raja ; Khan, A.I.
Author_Institution :
Clayton Sch. of IT, Monash Univ., Clayton, VIC
Abstract :
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.
Keywords :
Hopfield neural nets; computational complexity; content-addressable storage; pattern recognition; Hopfield network algorithm; associative memory; comparative analysis; computational complexity; distributed hierarchical graph neuron; pattern recognition algorithms; recall efficiency; Associative Memory; Distributed Hierarchical Graph Neuron; Hopfield Network; Pattern Recognition;
Conference_Titel :
Computer and Information Technology Workshops, 2008. CIT Workshops 2008. IEEE 8th International Conference on
Conference_Location :
Sydney, QLD
Print_ISBN :
978-0-7695-3242-4
Electronic_ISBN :
978-0-7695-3239-1
DOI :
10.1109/CIT.2008.Workshops.65
