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This invention discloses a time series completion method, device, and medium based on diffusion sampling correction and frequency domain optimization. The method includes: constructing an observation mask; inputting the complete time series and the corresponding simulated missing mask into a diffusion model, generating an original noise sequence through forward diffusion, and generating a perturbation noise sequence based on step-dependent Gaussian perturbation, using the perturbation noise sequence as model input, and using the original noise sequence as a supervisory signal to train a diffusion noise predictor; in the inference phase, inputting the time series containing partial observations and the corresponding real missing mask into the trained diffusion noise predictor, iteratively generating intermediate samples according to a preset diffusion step size, performing frequency domain decomposition and correction on the intermediate samples during the iteration process, and continuing subsequent iterations based on the corrected signal until all preset diffusion steps are completed; and outputting the completed time series data. This invention achieves the completion of missing data in multivariate time series.