Fourier-KAN-Mamba: A Novel State-Space Equation Approach for Time-Series Anomaly Detection

ArXi:2511.15083v2 Announce Type: replace Time-series anomaly detection plays a critical role in numerous real-world applications, including industrial monitoring and fault diagnosis. Recently, Mamba-based state-space models have shown remarkable efficiency in long-sequence modeling. However, directly applying Mamba to anomaly detection tasks still faces challenges in capturing complex temporal patterns and nonlinear dynamics.