Multiple-target tracking (MTT) in the presence of spurious measurements poses difficult computational challenges related to the measurement-to-track data association problem. Different approaches have been proposed to tackle this problem, including various approximations and heuristic optimization tools. The Cross Entropy (CE) and the related Parametric MinxEnt (PME) methods are recent optimiza...

Because of its complexity, reliability analysis of lifeline-network usually employs a sampling-based approach. MonteCarlo simulation (MCS) provides a straightforward method to deal with interdependence between structural components and their cascading failures in the lifeline network system, but its computational cost might be expensive if the probability of the event of interest is too low. To...

Multiple-target tracking (MTT) in the presence of spurious measurements poses difficult computational challenges related to the measurement-to-track data association problem. Different approaches have been proposed to tackle this problem, including various approximations and heuristic optimization tools. The Cross Entropy (CE) and the related Parametric MinxEnt (PME) methods are recent optimiza...

Multiple-target tracking (MTT) in the presence of spurious measurements poses difficult computational challenges related to the measurement-to-track data association problem. Different approaches have been proposed to tackle this problem, including various approximations and heuristic optimization tools. The Cross Entropy (CE) and the related Parametric MinxEnt (PME) methods are recent optimiza...

The Cross-Entropy Ant System (CEAS) is an Ant Colony Optimization (ACO) system for distributed and online path management in telecommunication networks. Previous works on CEAS have enhanced the system by introducing new features. This paper takes a step back and revisits the auto-regressive functions at the core of the system. These functions are approximations of complicated transcendental fun...

Article history: Received 22 December 2006 Received in revised form 7 March 2008 Accepted 19 March 2008

Entropy measures have been extensively used to assess heart rate variability (HRV), a noninvasive marker of cardiovascular autonomic regulation. It is yet to be elucidated whether those entropy measures can sensitively respond to changes of autonomic balance and whether the responses, if there are any, are consistent across different entropy measures. Sixteen healthy subjects were enrolled in t...

We propose a regularized sequence-level (SEQ) deep neural network (DNN) model adaptation methodology as an extension of the previous KL-divergence regularized cross-entropy (CE) adaptation [1]. In this approach, the negative KL-divergence between the baseline and the adapted model is added to the maximum mutual information (MMI) as regularization in the sequence-level adaptation. We compared ei...

An improved cross-entropy (CE) method assisted with a chaotic operator (CGSCE) is presented for solving the optimal power flow (OPF) problem. The introduction of helps to enhance exploration capability popular approach while global best solution preserved. To handle constraints in flow, an efficient constraint handling technique no parameter adjustment also introduced. tested on both IEEE-30 bu...

The study proposes the contemporaneous assessment of conditional entropy (CE) and self-entropy (sE), being the two terms of the Shannon entropy (ShE) decomposition, as a function of the time scale via refined multiscale CE (RMSCE) and sE (RMSsE) with the aim at gaining insight into cardiac control in long QT syndrome type 1 (LQT1) patients featuring the KCNQ1-A341V mutation. CE was estimated vi...