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Linjiang Zheng

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Conference Open access Sep 2026

SMLDR: Spectral Memory Learner with Dual-Retrieval for Time Series Forecasting

This paper re-examines frequency-domain modeling from the perspective of spectral non-identifiability and proposes a Spectral Memory Learner with Dual Retrieval (SMLDR) for time series forecasting, which represents periodic components as reusable spectral prototypes stored in learnable memory.

Zhenxin Li, Longquan Liao, Wen-Chang Zhang et al. · 0 citations

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