FCAE-Mixer: frequency-aware convolutional autoencoder with dual-branch mixing for time series anomaly detection
The model innovatively combines a one-dimensional convolutional autoencoder and a multi-layer perceptron to extract local temporal transient features and global variable spatial mappings, respectively, and an FFT-Attention module is introduced to enhance adaptive focus on low-frequency spectral modes while suppressing...