Second-order negative-curvature methods for box-constrained and general constrained optimization

A Nonlinear Programming algorithm that converges to second-order stationary points is introduced in this paper. The main tool is a second-order negative-curvature method for box-constrained minimization of a certain class of functions that do not possess continuous second derivatives. This method is used to define an Augmented Lagrangian algorithm of PHR (Powell-Hestenes-Rockafellar) type. Convergence proofs under weak constraint qualifications are given. Numerical examples showing that the new method converges to second-order stationary points in situations in which first-order methods fail are exhibited.

Second-order model for remote and close-up short-circuit faults currents on DC traction supply

A technique to calculate the current waveform for both close-up and remote short-circuit faults on DC supplied railways and subways is presented. Exact DC short-circuit current calculation is best performed by sophisticated computer transient simulations. However, an accurate simplified calculation method based on second-order approximation which can be easily executed with the help of a calculator or a spreadsheet program is proposed.

Oscillation for a second-order neutral differential equation with impulses

We consider a certain type of second-order neutral delay differential systems and we establish two results concerning the oscillation of solutions after the system undergoes controlled abrupt perturbations (called impulses). As a matter of fact, some particular non-impulsive cases of the system are oscillatory already. Thus, we are interested in finding adequate impulse controls under which our system remains oscillatory. (C) 2009 Elsevier Inc. All rights reserved.

Recording from Two Neurons: Second-Order Stimulus Reconstruction from Spike Trains and Population Coding

We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5% of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100% improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.

A numerical investigation of the atmosphere-ocean thermal contrast over the coastal upwelling region of Cabo Frio, Brazil

An one-dimensional atmospheric second order closure model, coupled to an oceanic mixed layer model, is used to investigate the short term variation of the atmospheric and oceanic boundary layers in the coastal upwelling area of Cabo Frio, Brazil (23 degrees S, 42 degrees 08`W). The numerical simulations were carried out to evaluate the impact caused by the thermal contrast between atmosphere and ocean on the vertical extent and other properties of both atmospheric and oceanic boundary layers. The numerical simulations were designed taking as reference the observations carried out during the passage of a cold front that disrupted the upwelling regime in Cabo Frio in July of 1992. The simulations indicated that in 10 hours the mechanical mixing, sustained by a constant background flow of 10 in s(-1), increases the atmospheric boundary layer in 214 in when the atmosphere is initially 2 K warmer than the ocean (positive thermal contrast observed during upwelling regime). For an atmosphere initially -2 K colder than the ocean (negative thermal contrast observed during passage of the cold front), the incipient thermal convection intensifies the mechanical mixing increasing the vertical extent of the atmospheric boundary layer in 360 in. The vertical evolution of the atmospheric boundary layer is consistent with the observations carried out in Cabo Frio during upwelling condition. When the upwelling is disrupted, the discrepancy between the simulated and observed atmospheric boundary layer heights in Cabo Frio during July of 1992 increases considerably. During the period of 10 hours, the simulated oceanic mixed layer deepens 2 in and 5.4 in for positive and negative thermal contrasts of 2 K and -2 K, respectively. In the latter case, the larger vertical extent of the oceanic mixed layer is due to the presence of thermal convection in the atmospheric boundary layer, which in turn is associated to the absence of upwelling caused by the passage of cold fronts in Cabo Frio.

Pseudolikelihood equations for Potts MRF model parameter estimation on higher order neighborhood systems

This letter presents pseudolikelihood equations for the estimation of the Potts Markov random field model parameter on higher order neighborhood systems. The derived equation for second-order systems is a significantly reduced version of a recent result found in the literature (from 67 to 22 terms). Also, with the proposed method, a completely original equation for Potts model parameter estimation in third-order systems was obtained. These equations allow the modeling of less restrictive contextual systems for a large number of applications in a computationally feasible way. Experiments with both simulated and real remote sensing images provided good results.