We present theoretical results pertaining to the ability of ℓp minimization to recover sparse and compressible signals from incomplete and noisy measurements. In particular, we ...
In this note, we address the theoretical properties of p, a class of compressed sensing decoders that rely on p minimization with p (0, 1) to recover estimates of sparse and compr...
—In this paper, we introduce a sparse approximation property of order s for a measurement matrix A: xs 2 ≤ D Ax 2 + β σs(x) √ s for all x, where xs is the best s-sparse app...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
— Closed-loop, asymptotically stable walking motions are designed for a 5-link, planar bipedal robot model with one degree of underactuation. Parameter optimization is applied to...