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We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are considered. The asymptotic distortion-rate functions are obtained when the measurement matrix belongs to certain random matrix ensembles. Furthermore, we adapt two well-known compressive sensing reconstruction algorithms to accommodate the quantization effects. The performance of the new reconstruction methods is assessed through extensive computer simulations.

Distortion-rate functions for quantized compressive sensing