On the direct determination of constrained pure state one-electron density matrices: II. A modified algorithm and its applications

An algorithm recently proposed by us for the direct determination of pure state one-electron density matrices (P) under externally imposed constraints has been remodelled. The modified algorithm is applied to the construction of ground state potential energy curve of lithium hydride molecule usingknown values of dipole moments of LiH at various internuclear distances as theexternal constraint. The equilibrium internuclear distances (R _c) is seen to be unaffected by the constraint, but the force constant improves remarkably. The relevant features of the constrained density vis-a-vis those of the unconstrained one are analyzed revealing some of the improved features of the constrained density.     

Blind image deconvolution subject to bandwidth and total variation constraints

We present a maximum likelihood (ML) deconvolution algorithm with bandwidth and total variation (TV) constraints for degraded image due to atmospheric turbulence. The bandwidth limit function is estimated in view of optical system parameters and Fourier optical theory. With the aid of bandwidth and TV minimization as compelling constraints, the algorithm can not only suppress noise effectively but also restrict the bandwidth of point-spread function (PSF) that may lead to trivial solution. Compared with the conventional ML method, the proposed algorithm is able to restore a noise-free image, and the detailed texture is better than that of ML.     

结合稀疏编码和空间约束的红外图像聚类分割研究

提出了结合稀疏编码和空间约束的红外图像聚类分割新算法, 在稀疏编码的基础上融合聚类算法, 扩展了传统的基于K-means聚类的图像分割方法. 结合稀疏编码的聚类分割算法能有效融合图像的局部信息, 便于利用像素之间的内在相关性, 但是对于分割会出现过分割和像素难以归类的问题.为此, 在字典的学习过程中, 将原子的聚类算法引入其中, 有助于缩减字典中原子所属类别的数目, 防止出现过分割; 考虑到像素及其邻域像素具有类别属性一致性的特点, 引入了空间类别属性约束信息, 并给出了一种交替优化算法. 联合学习字典、稀疏系数、聚类中心和隶属度, 将稀疏编码系数同原子对聚类中心的隶属程度相结合, 构造像素归属度来判断像素所属的类别. 实验结果表明, 该方法能够有效提高红外图像重要区域的分割效果, 具有较好的鲁棒性. 关键词： 图像分割 稀疏编码 聚类 空间约束     

Augmented Algorithm for Generation of Constraints

It is found that Dirac's original consistency conditions do not suffice to generate all the secondary constraints and determine all the multipliers in front of the second-class constraints for the general singular Lagrangian sys tems. Cawley 's second counter example of Dirac's conjecture just has this feature. This may lead to the fact that the equivalence of Lagrangian and Hamiltonian formalism is not guaranteed and even dynamics of Hamil tonian formalism is not completely determined. In order to overcome the above difficulties, an augmen ted algorithm for generation of constraints-the algorithm of the extended consistency conditions is proposed. In this new algorithm, Cawley's second example is no longer a counter example of Dirac's conjecture.     

A novel power allocation strategy for cooperative PDMA systems

Cooperative communication technology is of great importance for increasing the user reachable rate, further improving throughput and reducing the outage probability of non-orthogonal multiple access (NOMA) systems. This paper mainly studies the power allocation optimization method based on amplify-and-forward (AF) pattern division multiple access (PDMA) to obtain the maximum achievable throughput. We formulate an optimization problem of user power allocation in a downlink PDMA system with cooperative relaying, the exact expressions of system throughput and user outage probability of the AF-PDMA system are derived, and a novel power allocation optimization method based on uniform distribution and restricted constraints is proposed. The effectiveness of the restricted constraints and optimization method is verified by theoretical analysis and simulation. The studies we have performed showed that the proposed scheme with uniform distribution and restricted constraints can be significantly improved in terms of the system throughput in comparison to the case with a genetic algorithm (GA) and fixed power allocation scheme. Concerning the proposed method, the search space is reduced to 1/3 of the original feasible region, and the runtime of the algorithm accounts for only 20% of the GA runtime.     

Truss optimization on shape and sizing with frequency constraints based on orthogonal multi-gravitational search algorithm

Structural optimization on shape and sizing with frequency constraints is well-known as a highly nonlinear dynamic optimization problem with several local optimum solutions. Hence, efficient optimization algorithms should be utilized to solve this problem. In this study, orthogonal multi-gravitational search algorithm (OMGSA) as a meta-heuristic algorithm is introduced to solve truss optimization on shape and sizing with frequency constraints. The OMGSA is a hybrid approach based on a combination of multi-gravitational search algorithm (multi-GSA) and an orthogonal crossover (OC). In multi-GSA, the population is split into several sub-populations. Then, each sub-population is independently evaluated by an improved gravitational search algorithm (IGSA). Furthermore, the OC is used in the proposed OMGSA in order to find and exploit the global solution in the search space. The capability of OMGSA is demonstrated through six benchmark examples. Numerical results show that the proposed OMGSA outperform the other optimization techniques.     

Optimization of semiconductor quantum devices by evolutionary search

A novel simulation strategy is proposed for searching for semiconductor quantum devices that are optimized with respect to required performances. Based on evolutionary programming, a technique that implements the paradigm of genetic algorithms in more-complex data structures than strings of bits, the proposed algorithm is able to deal with quantum devices with preset nontrivial constraints (e.g., transition energies, geometric requirements). Therefore our approach allows for automatic design, thus avoiding costly by-hand optimizations. We demonstrate the advantages of the proposed algorithm through a relevant and nontrivial application, the optimization of a second-harmonic-generation device working in resonance conditions.     

红外目标湍流退化图像的优化复原算法

提出了基于最速下降法的湍流退化图像盲目复原算法。将图像转换到频域中，建立一个基于目标图像和点扩展函数频谱的目标函数，通过迭代方式采用最速下降优化方法来极小化该目标函数，并利用傅里叶变换和反变换将目标图像和点扩展函数在频域和空域之间进行变换，在每次迭代中交替加入约束条件进行反复修正，以便取得预期的图像恢复效果，增强算法的稳定性和抗噪能力。针对红外目标湍流退化图像，在微机上对算法进行了一系列复原验证实验。实验结果表明：该文算法复原效果稳定，抗噪能力强，具有实用价值。     

激光跟踪测量系统自校正方法研究

建立了测量系统运动学模型。针对以往在球坐标激光跟踪系统中参考点只能借助于外部更高精度的仪器来校正的缺点,提出了平面约束自校正方法,并对系统进行了自校正研究。仿真结果表明了该方法的有效性。     

An iterative method for improving the quality of reconstruction of a three-dimensional surface

A complex image with constraints imposed on the amplitude and phase image components is processed using the Gerchberg iterative algorithm for the first time. The use of the Gerchberg iterative algorithm makes it possible to improve the quality of a three-dimensional surface profile reconstructed by the previously proposed method that is based on the multiangle projection of fringes and the joint processing of the obtained images by Fourier synthesis.     

Single frame blind image deconvolution by non-negative sparse matrix factorization

Novel approach to single frame multichannel blind image deconvolution has been formulated recently as non-negative matrix factorization problem with sparseness constraints imposed on the unknown mixing vector that accounts for the case of non-sparse source image. Unlike most of the blind image deconvolution algorithms, the novel approach assumed no a priori knowledge about the blurring kernel and original image. Our contributions in this paper are: (i) we have formulated generalized non-negative matrix factorization approach to blind image deconvolution with sparseness constraints imposed on either unknown mixing vector or unknown source image; (ii) the criteria are established to distinguish whether unknown source image was sparse or not as well as to estimate appropriate sparseness constraint from degraded image itself, thus making the proposed approach completely unsupervised; (iii) an extensive experimental performance evaluation of the non-negative matrix factorization algorithm is presented on the images degraded by the blur caused by the photon sieve, out-of-focus blur with sparse and non-sparse images and blur caused by atmospheric turbulence. The algorithm is compared with the state-of-the-art single frame blind image deconvolution algorithms such as blind Richardson-Lucy algorithm and single frame multichannel independent component analysis based algorithm and non-blind image restoration algorithms such as multiplicative algebraic restoration technique and Van-Cittert algorithms. It has been experimentally demonstrated that proposed algorithm outperforms mentioned non-blind and blind image deconvolution methods.     

Motion detection in moving background using a novel algorithm based on image features guiding self-adaptive Sequential Similarity Detection Algorithm

A novel efficient algorithm for motion detection in dynamic background was proposed. In image registration step, a feature-based and self-adaptive Sequential Similarity Detection Algorithm (SSDA) algorithm was proposed, which searches for matching position under constraints induced by image features with variational threshold. Then perform change detection by calculating and classifying the Mean Absolute Difference (MAD) around detected features in the middle frames of three consecutive images. Moving objects position was determined according to the rule that the feature from moving regions shows a lager MAD. Experiments on data sets of four typical scenes show that the improved registration algorithm is accurate and costs less than 0.4 s in computation, much faster compared with other four methods, and the proposed Dual Maximum Mean Absolute Difference Algorithm (DMMADA) can obtain a robust set of moving object features. Our algorithm can be used for fast detection of moving targets in dynamic background as well as change detection.     

基于波段子集特征提取的最小二乘支持向量机高光谱图像分类技术

针对高光谱图像分类,文章提出一种基于波段子集最大噪声分量特征提取的最小二乘支持向量机的高光谱图像分类算法.利用高光谱图像的谱间相关性将原始光谱波段划分为若干个波段子集,并在各个子集上采用最大噪声分量方法进行特征提取,将提取的特征合成为分类的组合特征矢量,避免了高光谱图像较强的波段相关性,减少了谱间冗余.并且采用了最小二...     

A SYNTHETIC ANALYSIS ON DESIGN OF OPTIMUM CONTROL FOR AN OPTIMIZED INTELLIGENT STRUCTURE

A hybrid optimization algorithm is developed to minimize the control energy and the structural weight under the constraints of the structural dynamic property requirements. A 72-bar space truss with two piezoelectric actuators is used to illustrate the complete process of this algorithm. It is shown that the control energy and the structural weight are clearly reduced using the proposed method.     

基于约束优化的闪光照相图像重建算法

针对闪光照相图像受模糊及噪声影响的问题,提出了一种基于约束优化的闪光照相图像重建算法。该算法建立基于平行束投影的正向成像矩阵,并通过嵌入模糊矩阵表达成像过程中的模糊因素,采用最速下降法求解重建问题。在算法中设计了预优矩阵以提高迭代重建速度,利用客体密度值非负、密度分布分段光滑并含有阶跃性边界的先验知识,设计和采用了非负约束、光滑约束及广义变分边界约束条件。对仿真FTO客体图像及实际闪光照相图像的重建结果表明,基于约束优化的重建算法具有良好的边界保持能力及噪声抑制能力,可以有效提高图像重建质量。     

The admissible portfolio selection problem with transaction costs and an improved PSO algorithm

In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.     

Cooperatively surrounding control for multiple Euler–Lagrange systems subjected to uncertain dynamics and input constraints

In this paper, we investigate cooperatively surrounding control(CSC) of multi-agent systems modeled by Euler–Lagrange(EL) equations under a directed graph. With the consideration of the uncertain dynamics in an EL system, a backstepping CSC algorithm combined with neural-networks is proposed first such that the agents can move cooperatively to surround the stationary target. Then, a command filtered backstepping CSC algorithm is further proposed to deal with the constraints on control input and the absence of neighbors' velocity information. Numerical examples of eight satellites surrounding one space target illustrate the effectiveness of the theoretical results.     

Restoration of atmospheric turbulence degraded images

A blind image deconvolution algorithm in the frequency domain is proposed which uses the edge-preserving method and generic bandwidth of optical system. Generic bandwidth of optical system is analyzed. With the benefits of bandwidth and edge-preserving method as compelling constraints, the algorithm cannot only suppress noise effectively but also restrict the bandwidth of point-spread function (PSF), so high-quality result can be obtained. The new algorithm is superior in handling unregistered channels. The performance of this approach is investigated with simulated data. As shown in our investigation, the algorithm can significantly alleviate the artifacts produced by the deconvolution process.     

High-performance algorithm for calculating non-spurious spin- and parity-dependent nuclear level densities

A new high-performance algorithm for calculating the spin- and parity-dependent shell model nuclear level densities using methods of statistical spectroscopy in the proton-neutron formalism was recently proposed. When used in valence spaces that cover more than one major harmonic oscillator shell, this algorithm mixes the genuine intrinsic states with spurious center-of-mass excitations. In this Letter we present an advanced algorithm, based on the recently proposed statistical moments method, that eliminates the spurious states. Results for unnatural parity states of several sd-shell nuclei are presented and compared with those of exact shell model calculations and experimental data.     

基于NURBS曲线直接插补算法的嵌入式数控系统设计与实现

提出了一种结合486SX级别的X86微处理器和可编程逻辑器件CPLD两级控制的嵌入式数控系统设计方案,阐述了该系统的硬件接口电路设计;提出了基于改进S形加减速的NURBS曲线直接插补算法,在满足最大弦高误差、最大法向加速度以及最大进给速度要求的情况下,对插补曲线的加速段和减速段进行速度规划。最后采用基于该插补算法的嵌入式数控系统,在半圆形毛坯上进行了五角星NURBS曲线的实际加工,验证了所设计嵌入式数控系统的可行性和有效性,具有一定的工程应用价值。