In this paper, we analyze the convergence of the alternating direction method of multipliers
(ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, ϕ (x_0 …

Vibration monitoring is one of the most effective ways for bearing fault diagnosis, and a
challenge is how to accurately estimate bearing fault signals from noisy vibration signals. In …

Iterative shrinkage/thresholding algorithm (ISTA) is a well-studied method for finding sparse
solutions to ill-posed inverse problems. In this letter, we present a data-driven scheme for …

Diagnosing the bearing fault, especially incipient fault is important for equipment health
management while is still a challenge in which high-fidelity extraction of the fault signature is …

In numerous applications, such as DNA microarrays, face recognition, and spectral
unmixing, we need to acquire a non-negative K-sparse signal x from an underdetermined …

In this paper, we propose an algorithmic framework, dubbed inertial alternating direction
methods of multipliers (iADMM), for solving a class of nonconvex nonsmooth multiblock …

Sparse recovery has attracted considerable attention in signal processing community these
years, because of its widespread usage in many applications. Though lots of convex and …

Frequency agility increases the difficulty of jammers to predict and estimate the carrier
frequency and, thus, improves the radar electronic counter-countermeasures (ECCM) …

This paper proposes vector minimax concave (VMC) penalty for sparse representation using
tools of Moreau envelope. The VMC penalty is a weighted MC function; by fine tuning the …

By embedding an ℓ p-norm noise constraint for p≥ 2 into the recently emerged ℓ 1-2
method, in this letter, we study theoretically and numerically an ℓ 1-2/ℓ p method for recovery …