期刊
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
卷 38, 期 6, 页码 1525-1536出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCB.2008.927717
关键词
Autoassociative memory; cellular neural networks (CNNs); cloning template; heteroassociative memory
类别
资金
- Hong Kong Research Grants Council [CUH K4176/08E]
- Natural Science Foundation of China [Grant 6077405 1]
- Program for New Century Excellent Talents in Universities of China [NCET-06-0658]
- Fok Ying Tung Education Foundation [111068]
This paper presents a design method for synthesizing associative memories based on discrete-time recurrent neural networks. The proposed procedure enables both hetero- and auto-associative memories to be synthesized with high storage capacity and assured global asymptotic stability. The stored patterns are retrieved by feeding probes via external inputs rather than initial conditions. As typical representatives, discrete-time cellular neural networks (CNNs) designed with space-invariant cloning templates are examined in detail. In particular, it is shown that procedure herein can determine the input matrix of any CNN based on a space-invariant cloning template which involves only a few design parameters. Two specific examples and many experimental results are included to demonstrate the characteristics and performance of the designed associative memories.
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