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arXiv · 2310.15119

Compressed Sensing of Generative Sparse-latent (GSL) Signals

Antoine Honoré·Anubhab Ghosh·Saikat Chatterjee
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Abstract

We consider reconstruction of an ambient signal in a compressed sensing (CS) setup where the ambient signal has a neural network based generative model. The generative model has a sparse-latent input and we refer to the generated ambient signal as generative sparse-latent signal (GSL). The proposed sparsity inducing reconstruction algorithm is inherently non-convex, and we show that a gradient based search provides a good reconstruction performance. We evaluate our proposed algorithm using simulated data.

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Antoine Honoré, Anubhab Ghosh, Saikat Chatterjee. 2023-10-16. Compressed Sensing of Generative Sparse-latent (GSL) Signals. https://arxiv.org/abs/2310.15119

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