Estimation of distribution algorithm (EDA) is a kind of EAs, which is based on the technique of probabilistic model and sampling. Large scale optimization problems are a challenge for the conventional EAs. This paper presents an adaptive learning rate elitism EDA combining chaos perturbation (ALREEDA) to improve the performance of traditional EDA to solve high dimensional optimization problems....

Conditions for observability of a linearized smoothairgap induction machine model are examined, and limitations of any speed-sensorless observer scheme based on such a model are discussed. An approach for speed-sensorless flux estimation based on singular perturbation theory is developed. This approach relies on the natural time-scale separation between the electrical and mechanical dynamics of...

Traveltime calculations amount to solving the nonlinear eikonal equation for a given source location. We analyze the relationship between the eikonal solution and its perturbations with respect to the source location and develop a partial differential equation that relates the traveltime field for one source location to that for a nearby source. This linear first-order equation in one form depe...

Abstract: A hyperbolic iterated function system (IFS) whose attractor is the graph of a continuous function f : [a, b] × [c, d] → R that interpolates the given data in R is considered. The function f is called the bivariate fractal interpolation function (FIF) arising from the IFS and the graph of f which is a surface in R is called the bivariate fractal interpolation surface (FIS). By introduc...

To limit the radio map size and the time required to build the radio map, current WLAN location determination systems do not handle small-scale variations. This contributes to most of the estimation errors in the current systems. We propose a general technique, the perturbation technique, to handle the small-scale variations problem. The system uses user history to detect small-scale variations...

Context: Early size predictions (ESP) can lead to errors in effort predictions for software projects. This problem is particular acute in parametric effort models that give extra weight to size factors (for example, the COCOMO model assumes that effort is exponentially proportional to project size). Objective: Are effort estimates crippled by bad ESP? Method: Document inaccuracies in early size...

In this paper, we model complex signals by approximating the phase and the logarithm of the time-varying amplitude of the signal as a finite-order polynomial. We refer to a signal that has this form as an exponential polynomial signal (EPS). We derive an iterative maximum-likelihood (ML) estimation algorithm to estimate the unknown parameters of the EPS model. The initialization of the ML algor...

The evidence for the existance of an odderon [1] remains scarce. To date, the best evidence comes from the differential cross section in elastic pp and pp̄ scattering. The pp data show a dip structure at −t ≈ 1.3 GeV while the pp̄ data only flatten off at that point. The odderon, being odd under charge conjugation, couples with different signs to protons and antiprotons and can hence account for ...

0-7803-7651-X/03/$17.00 © 2003 IEEE Abstract— Harmonic plus noise model (HNM) divides the speech spectrum into two bands: harmonic and noise. One is modeled with harmonics of the fundamental and the other is simulated using random noise. As HNM analysis/synthesis is performed at each glottal closure instant (GCI), errors in estimation of GCIs affect the quality of the synthesized speech. The ob...