A Hierarchical Self-organizing Associative Memory for Machine Learning-Reference-Cited by-同舟云学术

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A Hierarchical Self-organizing Associative Memory for Machine Learning

Published:2007 Issue: Volume: Page:413-423
ISSN:0302-9743
Container-title:Advances in Neural Networks – ISNN 2007
language:
Short-container-title:

Author:

Starzyk Janusz A.,He Haibo,Li Yue

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-72383-7_49

Reference12 articles.

1. Chang, J.Y., Cho, C.W.: Second-order Asymmetric BAM Design with a Maximal Basin of Attraction. IEEE Trans. on System, Man, and Cybernetics, Part A: Systems and Humans 33, 421–428 (2003)

2. Salih, I., Smith, S.H., Liu, D.: Synthesis Approach for Bidirectional Associative Memories Based on the Perceptron Training Algorithm. Neurocomputing 35, 137–148 (2000)

3. Wang, L.: Multi-associative Neural Networks and Their Applications to Learning and Retrieving Complex Spatio-temporal Sequences. IEEE Trans. on System, Man, and Cybernetics, part B-Cybernetics 29, 73–82 (1999)

4. Hopfield, J.J.: Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proc. Nat. Acad. Sci. USA 79, 2554–2558 (1982)

5. Vogel, D.: Auto-associative Memory Produced by Disinhibition in a Sparsely Connected Network. Neural Networks 5(11), 897–908 (1998)

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