A Scalable Implementation of Sparse Approximation on a Field Programmable Analog Array

Compressed sensing is an important optimization problem in signal and image processing applications. A Hopfield-Network- like analog system is proposed as a solution, using the Locally Competitive Algorithm (LCA) [1] to solve an overcomplete l(1) sparse approximation problem. A scalable system architecture using sub-threshold currents is described. A 2x3 system is implemented on the RASP 2.9v chip, a Field Programmable Analog Array. The circuit successfully reproduced the outputs of a digital L1LS solver, converging to within 2.5% RMS error, and successfully matching its support vector. The paper concludes by discussing methods for scaling the architecture and including it in compressed sensing systems.