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This paper proposes Intelligent Partitioning for Self-supervised Denoising (iPSD), a method enabling unsupervised training of deep EEG denoisers by partitioning noisy segments without requiring clean reference data.
This article provides a detailed mathematical derivation of the Cooley-Tukey Fast Fourier Transform algorithm, explaining how it reduces the complexity of the Discrete Fourier Transform.
This paper proposes a framework for conditional generative compressed sensing, proving stable recovery bounds for prompt-conditioned models and demonstrating how prompt matching influences sampling distributions in experiments with Stable Diffusion.
This paper introduces LiVeAction, a lightweight neural codec designed for real-time operation on resource-constrained devices. It utilizes an FFT-like structure and variance-based rate penalty to achieve superior rate-distortion performance while remaining practical for low-power sensors.