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一种基于L1范数正则化的回声状态网络

DOI: 10.3724/SP.J.1004.2014.02428, PP. 2428-2435

Keywords: 回声状态网络,正则化,最小角回归,信息准则,多元时间序列

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Abstract:

?针对回声状态网络存在的病态解以及模型规模控制问题,本文提出一种基于L1范数正则化的改进回声状态网络.该方法通过在目标函数中添加L1范数惩罚项,提高模型求解的数值稳定性,同时借助于L1范数正则化的特征选择能力,控制网络的复杂程度,防止出现过拟合.对于L1范数正则化的求解,采用最小角回归算法计算正则化路径,通过贝叶斯信息准则进行模型选择,避免估计正则化参数.将模型应用于人造数据和实际数据的时间序列预测中,仿真结果证明了本文方法的有效性和实用性.

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