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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.