Restricted Boltzmann machine associative memory

Koki Nagatani; Masafumi Hagiwara

doi:10.1109/IJCNN.2014.6889573

Restricted Boltzmann machine associative memory

Koki Nagatani, Masafumi Hagiwara

Department of Information and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

Restricted Boltzmann machine associative memory (RBMAM) is proposed in this paper. RBMAM memorizes patterns using contrastive divergence learning procedure. It recalls by calculating the reconstruction of pattern using conditional probability. In order to examine the performance of the proposed RBMAM, extensive computer simulations have been carried out. As the result, it has shown that the performance of RBMAM is overwhelming compared with the conventional neural network associative memories. For example as for storage capacity, RBMAM can store about from 2N_hidden to AN_hideen patterns, where N_hidden denotes the number of neurons in the hidden layer. Similarly we have obtained superior performance of RBMAM in respect of noise tolerance and pattern complement.

Original language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3745-3750
Number of pages	6
ISBN (Electronic)	9781479914845
DOIs	https://doi.org/10.1109/IJCNN.2014.6889573
Publication status	Published - 2014 Sept 3
Event	2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China Duration: 2014 Jul 6 → 2014 Jul 11

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks

Other

Other	2014 International Joint Conference on Neural Networks, IJCNN 2014
Country/Territory	China
City	Beijing
Period	14/7/6 → 14/7/11

ASJC Scopus subject areas

Software
Artificial Intelligence

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10.1109/IJCNN.2014.6889573

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Restricted Boltzmann machine associative memory. / Nagatani, Koki; Hagiwara, Masafumi.

Proceedings of the International Joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers Inc., 2014. p. 3745-3750 6889573 (Proceedings of the International Joint Conference on Neural Networks).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nagatani, K & Hagiwara, M 2014, Restricted Boltzmann machine associative memory. in Proceedings of the International Joint Conference on Neural Networks., 6889573, Proceedings of the International Joint Conference on Neural Networks, Institute of Electrical and Electronics Engineers Inc., pp. 3745-3750, 2014 International Joint Conference on Neural Networks, IJCNN 2014, Beijing, China, 14/7/6. https://doi.org/10.1109/IJCNN.2014.6889573

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author = "Koki Nagatani and Masafumi Hagiwara",

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Restricted Boltzmann machine associative memory

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