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ART2wNF及其稳定性——可塑性动态平衡性能分析

DOI: 10.3724/SP.J.1004.2013.01381, PP. 1381-1388

Keywords: 稳定性-可塑性两难问题,幼态延续,自适应谐振理论,ART2网络,ART2wNF

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Abstract:

?稳定性-可塑性两难问题的核心是系统如何在不削弱或忘记已学习模式的同时,自适应地学习新事物.目前公认自适应谐振理论(Adaptiveresonancetheory,ART)能够部分解决稳定性-可塑性两难问题,但依然存在学习受样本输入顺序影响大,且存在学习中心渐变样本时,带来的所谓模式漂移的问题.受进化生物学关于人类学习的幼态延续特征的启发,本文为每个F2层节点配备活跃度指示器λ,并将其反馈回F1层参与STM(Shorttermmemory)向量的计算,使这种新型ART2网络在行为特征上具备幼态延续的显著特征,本文称之为ART2wNF(Adaptiveresonancetheorywithneotenyfeature).论文从理论上证明算法的可行性,并通过分析对随机生成样本集合的学习过程,对比了ART2wNF算法与常规ART2网络在可塑性、稳定性方面的差异以及ART2wNF在克服样本输入顺序影响等方面的优势.

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