We analyze proximal methods based on entropy-like distances for the minimization of convex functions subject to nonnegativity constraints. We prove global convergence results for the methods with approximate minimization steps and an ergodic convergence result for the case of finding a zero of a maximal monotone operator. We also consider linearly constrained convex problems and establish a qua...

We propose, as an alternative to current face recognition paradigms, an algorithm using reweighted l2 minimization, whose recognition rates are not only comparable to the random projection using l1 minimization compressive sensing method of Yang et al [5], but also robust to occlusion. Through numerical experiments, reweighted l2 mirrors the l1 solution [1] even with occlusion. Moreover, we pre...

The issues of waste generation in batch process plants differ in many aspects to continuous plants. Despite the smaller-scale of processing, complexities from unsteady state profiles, discontinuities, and run-to-run variations make waste minimization in batch plant more challenging. In this paper, we present a systematic methodology for waste minimization analysis of a batch process. The method...

We present a numerical minimization procedure to determine the macroscopic ‘plastic collapse strength’ of a tessellated cellular structure under a general stress state. The method is illustrated with sample cellular structures of regular and hierarchical honeycombs. Based on the deformation modes found by minimization of plastic dissipation, closed-form expressions for strength are derived. The...

The method of three stage weighted period analysis is generalized for simultaneous multichannel observations. The new method is based on the phase dispersion minimization over all channels simultaneously. The three stages in the full algorithm are phase dispersion minimization method (PDM), linear modeling (LM) and nonlinear modeling (NLM). Simple computational tests of the multichannel period ...

This paper is concerned with solving the Cauchy problem for an elliptic equation by minimizing an energy-like error functional and by taking into account noisy Cauchy data. After giving some fundamental results, numerical convergence analysis of the energy-like minimization method is carried out and leads to adapted stopping criteria for the minimization process depending on the noise rate. Num...

We present a novel sparse signal reconstruction method “ISD”, aiming to achieve fast reconstruction and a reduced requirement on the number of measurements compared to the classical `1 minimization approach. ISD addresses failed reconstructions of `1 minimization due to insufficient measurements. It estimates a support set I from a current reconstruction and obtains a new reconstruction by solv...