Buffered Block Forward Backward (BBFB) Method Applied to EM Wave Scattering from Homogeneous Dielectric Bodies

The iterative forward backward (FB) method has been proposed to solve the magnetic field integral equation for smooth one-dimensional rough surfaces. This method has proved to be very efficient, converging in a very small number of iterations. Nevertheless, this solution becomes unstable when some obstacle, like a ship or a large breaking wave, is included in the original problem. In this paper we propose a new extension of the FB method: the generalized forward backward (GFB) method, to solve such kinds of composite problems.

In this paper the convergence properties of the buffered block forward Backward (BBFB) method are investigated and shown to be independent of source position. The BBFB method is applied to the electric field integral equation (EFIE) for the case of a three-dimensional flat plate and wedge scatterer, at varying source locations. The convergence of the solution for the two problems, at each source location, is obtained and the corresponding iteration matrices for each scatterer computed. The numerical data provided in this paper illustrates and supports the conclusion that the source position does not affect the ability of the BBFB method to converge. Rather the convergence of the method is based on the geometry of the problem itself and the specific application of the BBFB algorithm to the problem.

To analyze EM scattering of a dielectric Target above the dielectric Gauss rough surface, a fast Cross Coupling iterative Approach is present in this paper. This algorithm combines the merit of both the bi-conjugate gradient method (Bi-CG) and forward backward method (FBM). At first, the electric field integral equations (EFIE) of the induced currents on the rough surface and the target are derived. An iterative approach was developed to solve the two EFIEs and scattering from both the target and underlying surface. The EFIE of the rough surface and the target are solved by using FBM and bi-conjugate gradient method (Bi-CG), respectively. The mutual effect between the rough surface and the target are implemented by iterative Calculation. The results of EM scattering form a dielectric cylinder above the dielectric Gauss rough surface showed that CCIA was well agreement with MOM. The accuracy, efficiency, and convergence of the method are then studied for rough surfaces with various parameters. The effect of these parameters for the scattering pattern was also discussed.

A computationally efficient algorithm, which combines the characteristic basis function method (CBFM), the physical optics (PO) approach (when applicable) with the forward backward method (FBM), is applied for the investigation of electromagnetic scattering fromand propagation overlarge-scale rough terrain problems. The algorithm utilizes high-level basis functions defined on macro-domains (blocks), called the characteristic basis functions (CBFs) that are constructed by aggregating low-level basis functions (i.e., conventional sub-domain basis functions). The FBM as well as the PO approach (when applicable) are used to construct the aforementioned CBFs. The conventional CBFM is slightly modified to handle large-terrain problems, and is further embellished by accelerating it, as well as reducing its storage requirements, via the use of an extrapolation procedure. Numerical results for the total fields, as well as for the path loss are presented and compared with either measured or previously published reference solutions to assess the efficiency and accuracy of the algorithm.

Spatial filter averaging approach of probabilistic method to linear second-order partial differential equations of the parabolic type

A robust and accurate iterative algorithm is proposed for the solution of electromagnetic wave scattering from 1-D layered rough surfaces. The forward–backward method (FBM) has been applied extensively for solving electromagnetic scattering from single-layer rough surfaces due to its rapid convergence rate. Nevertheless, the performance of the FBM deteriorates, as it is applied to layered random rough surface problems. The proposed method greatly improves the convergence rate of the FBM by applying a residual minimization step. The computational cost of the minimization step and the forward–backward sweeps is expedited by using the spectral acceleration. In this communication, the proposed algorithm is applied as a solution to the problem of electromagnetic wave scattering from layered rough surfaces. Numerical results are presented to demonstrate the better convergence properties of the proposed method as compared with the standard FBM. In addition, the proposed method is shown to be more robust than the FBM, especially as the distance between interfaces decreases. The computational complexity of the proposed algorithm is also presented and discussed.

In this paper, the topic of coherent two-dimensional direction of arrival (2D-DOA) estimation is investigated. Our study jointly utilizes the compressed sensing (CS) technique and the parallel profiles with linear dependencies (PARALIND) model and presents a 2D-DOA estimation algorithm for coherent sources with the uniform rectangular array. Compared to the traditional PARALIND decomposition, the proposed algorithm owns lower computational complexity and smaller data storage capacity due to the process of compression. Besides, the proposed algorithm can obtain autopaired azimuth angles and elevation angles and can achieve the same estimation performance as the traditional PARALIND, which outperforms some familiar algorithms presented for coherent sources such as the forward backward spatial smoothing-estimating signal parameters via rotational invariance techniques (FBSS-ESPRIT) and forward backward spatial smoothing-propagator method (FBSS-PM). Extensive simulations are provided to validate the effectiveness of the proposed CS-PARALIND algorithm.

Population Pharmacokinetic Analysis of the MDM2 Inhibitor KRT-232 (formerly AMG 232) in Subjects with Advanced Solid Tumors, Multiple Myeloma or Acute Myeloid Leukemia

Stepwise Multiple Regression Method to Forecast Fish Landing

The present study presents the classification of proteins by basing on its primary structures. The sequence of proteins collected in a file. The application of textmining technique for extracting the features is proposed. An algorithm is also developed which extracts all the n-grams existing in the file of data and produced a learning file. Algorithm supplies three files, Boolean file, that is a relation of existence or not existence, frequencies files and occurrences files. The applied forward selection and backward elimination method is a learning file with an accepted features numbers.

A novel reconstruction method from contours lines is provided. First, we use a simple method to get rid of redundant points on every contour, then we interpolate them by using cubic Bezier spline curve. For corresponding points of different contours, we interpolate them by the cubic Bezier spline curve too, so the whole surface can be reconstructed by the bi-cubic Bezier spline surface. The reconstructed surface is smooth because every Bezier surface is patched with G2 continuity, the reconstruction speed is fast because we can use the forward elimination and backward substitution method to solve the system of tridiagonal equations. We give some reconstruction examples at the end of this paper. Experiments showed that our method is applicable and effective.

In the age of 0–2 years, infants are introduced to foods. But parents could not give food carelessly because in this age infants are vulnerable to allergies. This condition causes parents to consider age and allergies in infant feeding. This application uses the forward chaining and backward chaining method to provide recommendations for infant nutrition in accordance with the age and allergies. The age and allergy constraints are used to make rules to give recommendations for any food ingredient fit the circumstances and determine whether the food is suitable to the infant's conditions. There are four most common types of allergies as the constraint in infant's feeding that is lactose intolerance, casein of cow's milk, egg and fish. Usability testing showed a good result namely 79.5 %.

We consider the problem of blind calibration of a sensor network, where the sensor gains and offsets are estimated from noisy observations of unknown signals. This is in general a nonidentifiable problem, unless restrictive assumptions on the signal subspace or sensor observations are imposed. We show that if each signal observed by the sensors follows a known dynamic model with additive noise, then the sensor gains and offsets are identifiable. We propose a dynamic Bayesian nonparametric model to infer the sensors' gains and offsets. Our model allows different sensor clusters to observe different unknown signals, without knowing the sensor clusters a priori. We develop an offline algorithm using block Gibbs sampling and a linearized forward filtering backward sampling method that estimates the sensor clusters, gains, and offsets jointly. Furthermore, for practical implementation, we also propose an online inference algorithm based on particle filtering and local Markov chain Monte Carlo. Simulations using a synthetic dataset, and experiments on two real datasets suggest that our proposed methods perform better than several other blind calibration methods, including a sparse Bayesian learning approach, and methods that first cluster the sensor observations and then estimate the gains and offsets.

An extended integral equation is developed for electromagnetic scattering from a perfectly conducting cylinder and a dielectric cylinder. The conventional surface integral equations cannot yield unique solutions when the wavenumber of the electromagnetic wave is equal to an eigenwavenumber of the system. Several methods to overcome this difficulty have been presented, but each method includes some drawbacks. A numerical method is proposed in which the boundary element method is applied to the extended integral equations with the observation points lying on a closed surface inside the scatterer. It is shown that the extended integral equations have unique solutions for any given wavenumber. As examples, plane wave scattering from a perfectly conducting elliptic cylinder, a dielectric elliptic cylinder, and a dielectric rectangular cylinder is numerically analyzed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An analytical solution for the bistatic electromagnetic (EM) scattering from an acoustically excited vibrating dielectric circular cylinder is presented. The incident acoustic wave causes a boundary deformation as well as a dielectric inhomogeneity within the dielectric cylinder. First, a perturbation method is developed to calculate the EM scattering from a slightly deformed and inhomogeneous dielectric cylinder. Then, assuming the vibration frequency is much smaller than the frequency of the incident EM wave, a closed form expression for the time-frequency response of the bistatic scattered field is obtained. The solution for acoustic scattering from an elastic cylinder is applied to give the displacement on the surface as well as the compression and dilation within the cylinder. Both the surface displacement and the variation in material density (dielectric constant fluctuation) within the cylinder contribute to the Doppler component of the EM scattered field. Results indicate that the Doppler frequencies correspond to the mechanical vibration frequencies of the cylinder and that the Doppler components only become sizeable near frequencies corresponding to the natural modes of free vibration in the cylinder. These resonances depend only on the object properties and are independent of the surrounding medium. Thus, utilizing the information in the Doppler spectrum scattered by an acoustically excited object vibrating at resonance could provide a means for buried object identification.