Motivated by the advantages achieved by implicit analogue net for solving online linear equations, a novel implicit neural model is designed based on conventional explicit gradient neural networks in this letter by introducing a positive-definite mass matrix. In addition to taking the advantages of the implicit neural dynamics, the proposed implicit gradient neural networks can still achieve gl...

We present a line search algorithm for minimizing nonconvex and/or nonsmooth objective functions. The algorithm is a hybrid between a standard Broyden-Fletcher-Goldfarb-Shanno (BFGS) and an adaptive gradient sampling (GS) method. The BFGS strategy is employed as it typically yields fast convergence to the vicinity of a stationary point, and along with the adaptive GS strategy the algorithm ensu...

RF pulse design via optimal control is typically based on gradient and quasi-Newton approaches and therefore suffers from slow convergence. We present a flexible and highly efficient method that uses exact second-order information within a globally convergent trust-region CG-Newton method to yield an improved convergence rate. The approach is applied to the design of RF pulses for single- and s...

While there is a growing body of research on which and how pitch features are perceived as attractive or likable, there are few studies investigating how the impression of a speaker as attractive or likable affects the speech behavior of his/her interlocutor. Recent studies have shown that perceived attractiveness and likability may not only have an effect on a speaker’s pitch features in isola...

The alternating direction method of multipliers (ADMM) has been successfully applied tosolve structured convex optimization problems due to its superior practical performance. Theconvergence properties of the 2-block ADMM have been studied extensively in the literature.Specifically, it has been proven that the 2-block ADMM globally converges for any penaltyparameter γ > 0. In th...

In (NAR 08/18 and 08/21, Oxford University Computing Laboratory, 2008) we introduced a second-derivative SQP method (S2QP) for solving nonlinear nonconvex optimization problems. We proved that the method is globally convergent and locally superlinearly convergent under standard assumptions. A critical component of the algorithm is the so-called predictor step, which is computed from a strictly ...

In this paper we describe an implementation of a 2dimensional DCT processor and shows that the GALS (Globally Asynchronous Locally Synchronous) approach is highly suitable for implementation of such processors. Primarily it increases the design efficiency by using the divide-and-conquer approach.

Dr. Afshari’s editorial gives insight on human nature (1). Collaborative willingness usually occurs when different sides perceive personal benefit, or when institutions mandate collaboration. This is not unique between higher and lower income countries; many working in global emergency medicine (EM) observe this within wealthier countries. It exists among collaborators in low resource settings....

In this paper convergence properties of piecewise affine (PWA) systems are studied. In general, a system is called convergent if all its solutions converge to some bounded globally asymptotically stable steady-state solution. The notions of exponential, uniform and quadratic convergence are introduced and studied. It is shown that for non-linear systems with discontinuous right-hand sides, quad...

We introduce and analyze some two-level multiplicative and additive Schwarz methods for variational and quasi-variational inequalities of the second kind. The methods are introduced as subspace correction algorithms for problems in a reflexive Banach space. We prove that these methods are globally convergent and give, under some assumptions, error estimates. In the finite element spaces, the in...