Robust Spectral Fuzzy Clustering of Multivariate Time Series with Applications to Electroencephalogram
多元时间序列的稳健谱模糊聚类及其脑电应用
Clustering multivariate time series (MTS) is challenging due to non-stationary cross-dependencies, noise contamination, and gradual or overlapping state boundaries. We introduce a robust fuzzy clustering framework in the spectral domain that leverages Kendall's tau-based canonical coherence to extract frequency-specific monotonic relationships across variables. Our method takes advantage of dominant frequency-based cross-regional connectivity patterns to improve clustering…