Under consideration is the large body of signal recovery problems that can be formulated as
the problem of minimizing the sum of two (not necessarily smooth) lower semicontinuous …

The hybrid steepest descent method is an algorithmic solution to the variational inequality
problem over the fixed point set of nonlinear mapping and applicable to broad range of …

This article presents a general tool for convexly constrained parameter/function estimation
both for classification and regression tasks, in a timeadaptive setting and in (infinite …

In this paper, the boundedness and complete stability of complex-valued neural networks
(CVNNs) with time delay are studied. Some conditions to guarantee the boundedness of the …

This paper exemplifies that the use of multiple kernels leads to efficient adaptive filtering for
nonlinear systems. Two types of multikernel adaptive filtering algorithms are proposed. One …

In this paper, the problem of distributed resource allocation with coupled equality, nonlinear
inequality and convex set constraints is studied. Each agent only has access to the …

This paper presents a novel projection-based adaptive algorithm for sparse signal and
system identification. The sequentially observed data are used to generate an equivalent …

This paper presents an algorithm, named adaptive projected subgradient method that can
minimize asymptotically a certain sequence of nonnegative convex functions over a closed …

In this paper, a variable step-size widely linear complex-valued affine projection algorithm
(VSS-WLCAPA) is proposed for processing noncircular signals. The variable step-size …

A block-iterative parallel decomposition method is proposed to solve general quadratic
signal recovery problems under convex constraints. The proposed method proceeds by …