Regularizing autoencoders with wavelet transform for sequence anomaly detection

Yueyue Yao, Jianghong Ma, Yunming Ye

Abstract: Highlights•Unsupervised model for sequence anomaly detection.•Propose a novel spectral regularizer to restrict latent spaces of autoencoders.•Statistical analysis on DWT coefficients to mine unique features of normal sequences.•Design a Weight Controller to gain sample-adaptive regularization weights.