Most natural signals are sparse in some basis; hence compressive sensing is a natural approach for information acquisition.
Compressive projections:
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Can be realized using inner products with binary coefficients, which is attractive for hardware implementation.
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Are expected to be resilient to a broad class of impairments.
Hence they are a promising approach for low-power front ends for downstream learning and inference.
We investigate the impact of real-world nonlinearities on compressive front ends, and study design changes needed to target deep learning applications.
Students
Soorya Gopalakrishnan
Faculty
Upamanyu Madhow, Naveen Verma (Princeton University)