Unmanned-aerial-vehicle (UAV)-assisted communications has attracted increasing attention
recently. This article investigates air–ground coordinated communications system, in which …

Compressed sensing in both noiseless, and noisy cases is considered in this article, and
uniform restricted isometry property (RIP) conditions for sparse signal recovery are …

The general Cauchy loss (GCL) criterion has been successfully proposed to improve the
performance of the Cauchy loss (CL) criterion for linear adaptive filtering in the presence of …

Recently, non-convex and non-linear metrics have been introduced in compressed sensing
to promote sparsity. This letter proposes an extension of the previously proposed …

The weighted ℓ r− ℓ 1 minimization method with 0< r≤ 1 largely generalizes the classical ℓ r
minimization method and achieves very good performance in compressive sensing …

In this paper, we establish new restricted isometry conditions for sparse signal recovery via ℓ
p (0< p≤ 1) minimization. For any t∈(1, 2], the restricted isometry constant (RIC) condition δ …

It is always an important problem to recover sparse signals from observations corrupted by
Gaussian noise and has been extensively investigated. In high-resolution maritime …

The null space property (-NSP) and restricted isometry property (RIP) are two important
frames for sparse signal recovery. New sufficient conditions in terms of-NSP and RIP are …

The kernel adaptive filters (KAFs) based on the minimum mean square error (MMSE)
criterion in reproducing kernel Hilbert space (RKHS) improve the performance of linear …

The null space property (-NSP) and restricted isometry property (RIP) are two important
frames for sparse signal recovery. New sufficient conditions in terms of-NSP and RIP are …