On the performance of cyclic moments-based parameter estimators ofamplitude modulated polynomial phase signals

Parameter estimation of amplitude-modulated polynomial phase signals embedded in additive white Gaussian noise is considered. The amplitude modulation is modeled as the sum of a real-valued deterministic function and a zero mean correlated stationary random process. It is shown that cyclic moments-based estimators, previously proposed for parameter estimation of polynomial phase signals modulated by stationary random processes, can be adapted to the more general signal model considered here. The covariance matrices of the cyclic moments-based amplitude and phase parameter estimators are derived for large sample lengths. Using this result, it is shown how the lags can be chosen to minimize the large-sample variances of the cyclic moments-based phase parameter estimators. Comparisons with the Cramer-Rao bounds are performed under the assumption of a Gaussian modulating process. The theoretical derivations are confirmed by simulation results     

Target Detection in Single- and Multiple-View Through-the-Wall Radar Imaging

A detector of targets behind walls and in enclosed structures is presented. The detector is applied to through-the-wall radar images obtained by wideband delay and sum beamforming. We consider the detection problem using single- and multiple-view imaging. The statistics of noise, clutter, and target images are examined and formulated using sample scenes. The effects of wall parameter errors on the image statistics are shown. An iterative detection scheme, which adapts itself to the image statistics, is presented. The proposed detection schemes are evaluated using real data.     

Estimation of SiC JFET temperature during short-circuit operations

This paper presents results showing the robustness of different SiC JFET transistors from SiCED in current limitation regime or short-circuit operation. Crystal temperature during failure was estimated after different electrical characterizations and using appropriate models of saturation current which is used as a thermal indicator. This work shows the exceptional robustness of SiC JFET transistors in current limitation mode compared to Si devices (MOSFETS and IGBTs).     

Efficient Subspace-Based Estimator for Localization of Multiple Incoherently Distributed Sources

In this paper, a new subspace-based algorithm for parametric estimation of angular parameters of multiple incoherently distributed sources is proposed. This approach consists of using the subspace principle without any eigendecomposition of the covariance matrix, so that it does not require the knowledge of the effective dimension of the pseudosignal subspace, and therefore the main difficulty of the existing subspace estimators can be avoided. The proposed idea relies on the use of the property of the inverse of the covariance matrix to exploit approximately the orthogonality property between column vectors of the noise-free covariance matrix and the sample pseudonoise subspace. The resulting estimator can be considered as a generalization of the Pisarenko's extended version of Capon's estimator from the case of point sources to the case of incoherently distributed sources. Theoretical expressions are derived for the variance and the bias of the proposed estimator due to finite sample effect. Compared with other known methods with comparable complexity, the proposed algorithm exhibits a better estimation performance, especially for close source separation, for large angular spread and for low signal-to-noise ratio.     

Functional Causality between Oil Prices and GDP Based on Big Data

This paper examines the causal relationship between oil prices and the Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia. The study is carried out by a data set collected quarterly, by Saudi Arabian Monetary Authority, over a period from 1974 to 2016. We seek how a change in real crude oil price affects the GDP of KSA. Based on a new technique, we treat this data in its continuous path. Precisely, we analyze the causality between these two variables, i.e., oil prices and GDP, by using their yearly curves observed in the four quarters of each year. We discuss the causality in the sense of Granger, which requires the stationarity of the data. Thus, in the first Step, we test the stationarity by using the Monte Carlo test of a functional time series stationarity. Our main goal is treated in the second step, where we use the functional causality idea to model the co-variability between these variables. We show that the two series are not integrated; there is one causality between these two variables. All the statistical analyzes were performed using R software.     

Synthesis of CdS Nanoparticles by Hydrothermal Method and Their Effects on the Electrical Properties of Bi-based Superconductors

Cadmium sulfide (CdS) nanoparticles were synthesized by hydrothermal process and have been characterized by x-ray diffraction (XRD), transmission electron microscopy (TEM), and energy-dispersive x-ray spectroscopy (EDXS) system. The effect of added CdS nanoparticles on the superconducting properties and flux pinning capability in (Bi,Pb)₂Sr₂Ca₂Cu₃O_y system (denoted as (Bi,Pb)-2223) has been reported. Hydrothermal method is an effective route to synthesize CdS nanoparticles with good crystallinity and having average grain size of about 12 nm. Then, small amounts (0–0.4 wt%) of nanosized CdS particles were added to Bi-2233 samples using a solid-state reaction route. The transport critical current densities and the electrical resistivity ρ(T, H) were performed using the four-probe technique. The results show that samples sintered by small amount of CdS nanoparticles (≤?0.3 wt%) exhibit the higher critical current densities and energy pinning in applied magnetic fields compared to free added sample. Consequently, the addition of CdS could introduce effective pinning centers which account for the improvement in superconducting properties in the Bi-2223 materials.     

Effect of pre-deposition annealing on physical properties of CZTSSe thin films deposed by RF-sputtering based on nanoparticles synthesized by solvothermal technique

This work aims to highlight the beneficial effect of annealing of Cu₂ZnSn(S,Se)₄ (CZTSSe) nanoparticles (NPs) on the properties of the obtained films by RF-magnetron sputtering at room temperature (RT) and at 200 °C. The CZTSSe targets used for the deposition are obtained using nanoparticles synthesized by solvothermal technique. It is denoted that the elemental composition of thin films becomes independent of the growth temperature in the case of annealed CZTSSe NPs. The optical investigation gives that the gap energy is ranging between 1.26 and 1.40 eV with an Urbach’s energy between 100 and 200 meV. By using the Wemple and Didominico model to analyze the refractive index spectra, we have identified common oscillator energy for all CZTSSe thin films and dispersion energy ranging from 2.63 to 5.81 eV. CZTSSe thin films obtained by means of annealed NPs exhibit higher dielectric constant and refractive index. The dispersion of different parameters with experimental conditions is analyzed via a common relationship that illustrates the linear dependence of n₀, E_d, ε_s, and ε_L on the square of the valence difference (ΔZ). The conductivity spectra are deduced, and a theoretical model was identified to fit the permittivity spectra. The obtained results are promising for solar cell applications.

     

Power and pressure effects upon magnetron sputtered aluminum doped ZnO films properties

In this work, polycrystalline aluminum doped zinc oxide (ZnO:Al) films with c-axis (002) orientation have been grown on glass and silicon substrates by RF (radio frequency) magnetron sputtering technique, at room temperature. A systematic study of the effect of sputtering deposition parameters (i.e. RF power and argon gas pressure) on the structural, optical and electrical properties of the films was carried out. We observed that, with increasing RF power the growth rate increased, while it decreased with increasing gas pressure. As mentioned above, the films were polycrystalline in nature with a strong preferred (002) orientation. The intrinsic compressive stress was found to decrease with both increasing RF power and gas pressure, and near stress-free film was obtained at 200 W RF power and 2 × 10^− 1 Pa gas pressure. The obtained ZnO:Al films, not only have an average transmittance greater than 90% in the visible region, but also have an optical band gap between 3.33 and 3.47 eV depending on the sputtering parameters. Moreover, a low value of the electrical resistivity (~ 1.25 × 10^− 3 Ω cm) was obtained for the film deposited at 200 W and 2 × 10^− 3 mbar.     

Accounting for input-model and input-parameter uncertainties in simulation

To account for the input-model and input-parameter uncertainties inherent in many simulations as well as the usual stochastic uncertainty, we present a Bayesian input-modeling technique that yields improved point and confidence-interval estimators for a selected posterior mean response. Exploiting prior information to specify the prior probabilities of the postulated input models and the associated prior input-parameter distributions, we use sample data to compute the posterior input-model and input-parameter distributions. Our Bayesian simulation replication algorithm involves: (i) estimating parameter uncertainty by randomly sampling the posterior input-parameter distributions; (ii) estimating stochastic uncertainty by running independent replications of the simulation using each set of input-model parameters sampled in (i); and (iii) estimating input-model uncertainty by weighting the responses generated in (ii) using the corresponding posterior input-model probabilities. Sampling effort is allocated among input models to minimize final point-estimator variance subject to a computing-budget constraint. A queueing simulation demonstrates the advantages of this approach.