Three-dimensional emission tomography of a scattering plasma

The three-dimensional emission ray tomography of a plasma partially scattering its self-radiation is considered. The spatial distribution of scattering density and its angular distribution are assumed to be known. The model of projection-data acquisition taking into account single and multiple scattering is constructed. In terms of this model, the problem of determining the distribution of local emission coefficients is posed. For solving this problem, the algorithm based on the Neumann-series expansion of the product of the radiative-transfer operator for a scattering medium and the operator for solving the pure emission problem was proposed. The algorithm was investigated in detail using numerical simulation.     

Localisation of moving sources in a multipath propagation environment

A new algorithm is presented for tracking correlated narrow-band sources in the presence of colored Gaussian noise. A fast cumulant-based preprocessing method is used to remove unknown noise and a Kalman filtering is used to track the source parameters. The use of a Kalman filtering avoids the data association problem and improves the tracking performance for crossing tracks. It is applied to the outputs of Newton’s algorithm to track moving sources. In this paper, the algorithm is developed for the special case in which the updated cumulant matrix is obtained by substituting a new matrix of the current data. The rank tracking problem is not considered in this study.We demonstrate the performance of the proposed algorithm by computer simulations of the tracking of moving targets emitting correlated signals, we also tested the proposed algorithm on the real data recorded during an underwater acoustic experiments.     

A Quantum Algorithm for Finding a Hamilton Circuit

A quantum algorithm for solving the classical NP-complete problem-the hamilton circuit is presented.The algorithm employs the quantum SAT and the quantum search algorithms.The algorithm is square-root faster than classical algorithm,and becomes exponentially faster than classical algoriothm if nonlinear quantum mechanical computer is used.     

Analysis of diffraction of a plane wave on a grating consisting of impedance bodies of revolution

The problem of wave scattering by a grating consisting of coaxial impedance bodies of revolution is solved. The efficient numerical algorithm based on the modified null field method is offered. The method is applied both to scalar and vector formulations of the problem. The numerical results are obtained for various geometries of the grating elements.     

Determination of temperature distribution and control parameter in a two-dimensional parabolic inverse problem with overspecified data

In this paper, we present a new algorithm to solve a two-dimensional parabolic inverse problem with a source parameter, which appears in many physical phenomena. A linearized compact difference scheme for this problem is constructed using the finite difference method. The discretization accuracy is second-order in time and fourth-order in space. We obtain the unique solvability and present an alternating direction implicit algorithm to solve this difference scheme. The results of numerical experiments are presented to demonstrate the accuracy of this algorithm.     

Active minimization of acoustic potential energy in a two-dimensional multimode waveguide

Acoustical Physics - The nonlinear inverse problem of active sound control in a two-dimensional waveguide is addressed. To solve the problem, a numerical algorithm based on an exhaustive search for...     

Number partitioning on a quantum computer

We present an algorithm to compute the number of solutions of the (constrained) number partitioning problem. A concrete implementation of the algorithm on an Ising-type quantum computer is given.     

Determination of the Coefficient of Light Absorption via Transformation of a Pulse in a Disperse Medium

We suggested and substantiated an algorithm for solving the inverse problem of determining the coefficient of absorption of light for the case of a disperse medium (body) V from the known time scans of the powers (fluxes) of radiation. The algorithm is based on strict integral relations and is applied when the coefficient of scattering, scattering indicatrix, and the optical dimensions of the body V are unknown. Using the properties of the solutions of direct boundary-value problems of radiation transfer theory and statistical modeling, the efficiency of the algorithm for disperse media of various configurations is shown.     

Structural source identification using a generalized Tikhonov regularization

This paper addresses the problem of identifying mechanical exciting forces from vibration measurements. The proposed approach is based on a generalized Tikhonov regularization that allows taking into account prior information on the measurement noise as well as on the main characteristics of sources to identify like its sparsity or regularity. To solve such a regularization problem efficiently, a Generalized Iteratively Reweighted Least-Squares (GIRLS) algorithm is introduced. Proposed numerical and experimental validations reveal the crucial role of prior information in the quality of the source identification and the performance of the GIRLS algorithm.     

Pricing model for equity warrants in a mixed fractional Brownian environment and its algorithm

This paper deals with the problem of pricing equity warrants in a mixed fractional Brownian environment. Based on the quasi-conditional expectation and the Fourier transform, we present the pricing model for equity warrants. Moreover, a hybrid intelligent algorithm, which is based on the Genetic Algorithm, is employed to solve the nonlinear optimization problem. The performance of our model and the proposed algorithm have been illustrated with some numerical examples.     

Parameter estimation for the piecewice-polynomial mean value trend of a stochastic time series

We consider the problem of mean value trend estimation for a stochastic time series in a mixture with noise. The trend is simulated as a polynomial function of time with parameters changing discontinuously at a random instant. The proposed solution of this problem is based on the optimal nonlinear filtering theory for pulsed Markovian processes. An algorithm for approximate estimation of piesewise-linear trend parameters is devised as an example. The results of numerical simulation of a synthesized algorithm are presented. Lobachevsky State University, Nizhny Novgorod, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 40, No. 11, pp. 1405–1415, November, 1997.     

Interlocked optimization and fast gradient algorithm for a seismic inverse problem

We give a nonlinear inverse method for seismic data recorded in a well from sources at several offsets from the borehole in a 2D acoustic framework. Given the velocity field, approximate values of the impedance are recovered. This is a 2D extension of the 1D inversion of vertical seismic profiles [18]. The inverse problem generates a large scale undetermined ill-conditioned problem. Appropriate regularization terms render the problem well-determined. An interlocked optimization algorithm yields an efficient preconditioning. A gradient algorithm based on the adjoint state method and domain decomposition gives a fast parallel numerical method. For a realistic test case, convergence is attained in an acceptable time with 128 processors.     

Optimization analysis of the thermal cloaking problem for a cylindrical body

The inverse heat transfer problem associated with constructing multilayer material shells cloaking the presence of a cylindrical body in an externally applied temperature field is studied. As the original mathematical model, the steady-state heat equation for an anisotropic shell is used. With the help of the optimization method, this inverse problem is reduced to the corresponding control problem. A numerical algorithm of its solution based on the particle swarm optimization is proposed, and the results of numerical experiments are discussed.     

基于遗传算法的混沌系统模糊控制

基于遗传算法，研究了混沌系统的模糊控制问题.采用遗传算法对模糊系统的隶属函数进行优化，综合了遗传算法强大的空间搜索能力，高精度和模糊控制器快速性的优点，使模糊控制达到较好的控制效果.仿真结果证明了所给方法的有效性. 关键词： 混沌系统 遗传算法 模糊控制     

Simulation of Local Error Correction of the Surface Shape by a Low-Dimensional Ion Beam

Technical Physics - We propose an algorithm for solving the problem of local error correction of the surface shape by a low-dimensional ion beam. The algorithm presumes successive sampling running...     

Maximum a posteriori deconvolution of sparse ultrasonic signals using genetic optimization

Deconvolution of sparse spike sequences has received much attention in the field of seismic exploration. In certain situations in ultrasonic non-destructive testing (NDT) of materials, similar conditions as those found in seismic exploration occur. One example is the problem of detecting disbonds in layered aluminum structures. The reflection sequence convolved with the impulse response of the transducer results in masking closely spaced reflections. Deconvolution of these signals may reveal the reflection sequence and thus make the interpretation easier. In this paper we use the Bernoulli-Gaussian (BG) distribution for modeling the signal generation. This relatively simple model allows maximum a posteriori (MAP) estimation of the reflection sequence. A derivation of the MAP criterion is given for clarity. We propose a genetic algorithm for optimizing the MAP criterion. The genetic algorithm approach is motivated by the fact that the criterion is non-convex, implying that the criterion may have more than one local minimum point. The probability of obtaining the global optimal solution is increased by using the proposed genetic algorithm. One of the key features in genetic algorithms, the so-called cross-over operator, has been modified and adapted to the structure of the BG deconvolution problem to improve the efficiency of the search. The algorithm is tested on simulated data using the probability of detection (PD) and probability of false alarm (PFA) as evaluation criteria. The algorithm is also tested on real ultrasonic data from a layered aluminum structure. The results show considerable improvements in the possibility of interpreting the signals.     

Determination of isoclinics in photoelasticity with a fast regularized estimator

The determination of isoclinics from photoelastic fringe patterns is a key problem in photoelasticity. Dealing with this problem, however, is not a simple task when isotropic points are present which is common for most experimental situations. Because of this, few researchers have proposed effective and practical solutions. Visualizing this problem as the problem of the determination of the modulo 2π fringe orientation, in this paper it is proposed an efficient regularized algorithm to solve it. Experimental results show that the proposal is effective and can be used with either monochromatic or white light.     

Parametric identification of a model for hydrogen transfer through double-layer membranes

A nonlinear inverse problem of determining the hydrogen permeability of double-layer membranes from experimental data is considered. The model includes both diffusion and adsorption/desorption processes. An identification algorithm is suggested.     

Inverse problem of a statistical estimation of scatterer characteristics and model examples

The inverse scattering problem involving experimental data with errors is considered in its statistical formulation. An algorithm for retrieving regularized estimates of the characteristics of spatially distributed scatterers (the phase velocity and absorption inhomogeneities) is developed. The algorithm takes into account the multiple scattering and generalizes the Wiener filtering to the nonlinear case. For weak scatterers, this nonlinear generalization is reduced to the linear Wiener filtering. The performance of the algorithm is verified by model examples simulating the operation of active acoustic tomography systems against various noise levels. The necessity of taking into account the multiple scattering and the fundamental role of the nonlinear filtering in the regularization procedure is demonstrated. It is remarkable that the noise robustness achieved in the reconstruction of strong scatterers with the optimal regularization algorithm is only slightly inferior to that achieved in the case of weak scatterers.     

声矢量圆阵相位模态域目标方位估计

为了实现矢量传感器在圆阵阵型下的应用,文中提出了一种适合于声矢量圆阵的目标方位估计算法。该算法首先将声矢量圆阵阵元域信号分解为一系列相互正交的相位模态,在相位模态域构造声压和质点振速的互协方差矩阵,然后进行MUSIC方位估计.理论分析和仿真结果表明,文中算法比相同阵型的声压阵MUSIC方位估计算法具有更好的噪声抑制能力、方位估计性能以及多目标分辨能力,试验结果也表明本文算法具有更好的噪声抑制能力以及更好的目标方位估计性能。该算法实现了声压和质点振速的相干处理,充分利用了声矢量传感器的平均声强抗噪原理,具有较强的抗各向同性噪声能力,并可以将子空间类DOA(Direction of Arrival)估计算法和相位模态域阵列信号处理技术有机结合起来,实现了声矢量传感器在圆阵阵型条件下的高分辨DOA估计。