Improved Chaotic Associative Memory for Successive Learning
DOI
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説明
In this research, we have proposed the Improved Chaotic Associative Memory for Successive Learning (ICAMSL). The proposed model is based on the Hetero Chaotic Associative Memory for Successive Learning with give up function (HCAMSL) (Arai & Osana, 2006) and the Hetero Chaotic Associative Memory for Successive Learning with Multi-Winners competition (HCAMSL-MW) (Ando et al., 2006). In the proposed ICAMSL, the learning process and recall process are not divided. When an unstored pattern is given to the network, the ICAMSL can learn the pattern successively. We carried out a series of computer experiments and confirmed that the proposed ICAMSL can learn patterns