Provided by:
National University of Singapore
Topic:
Hardware
Format:
PDF
Basis Pursuit DeNoising (BPDN) is an optimization method used in cutting edge computer vision and compressive sensing research. Although hosting a BPDN solver on an embedded platform is desirable because analysis can be performed in real-time, existing solvers are generally unsuitable for embedded implementation due to either poor run-time performance or high memory usage. To address the aforementioned issues, this paper proposes an embedded-friendly solver which demonstrates superior run-time performance, high recovery accuracy and competitive memory usage compared to existing solvers.
