Optimization of multiple region quantizer for Laplacian source

This paper proposes a multiple region quantizer composed of quantizers defined on different disjunctive regions of an input signal. In particular, for the two region and the three region cases, the paper provides a complete optimization of a multiple region companded quantizer for the Laplacian source of unit variance. The analysis of the multiple region quantizer is limited to a three region case due to the complexity of the optimization problem and due to the fact that much more complex multiple region quantizer models obtained for a higher number of regions could slightly improve the performances. Two-stage optimization is performed with respect to the number of reconstruction levels of each quantizer composing the considered multiple region companded quantizer and with respect to the region bounds. It is shown that optimal parameters depend only on the fractional part of the required average bit rate. In order to design the three region optimal quantizer, Lloyd–Max's algorithm and Newton–Kantorovich iterative method are used with the three region optimal companded quantizer as the initial solution. The gradient Newton–Kantorovich iterative method is used to provide better convergence speed than Lloyd–Max's algorithm, which is essential in cases where effective initialization solution of Lloyd–Max's algorithm is missing. It is shown that the three region optimal companded quantizer have signal to quantization noise ratio value close to the one of the three region optimal quantizer, where a simpler design procedure is the benefit of the three region optimal companded quantizer over the three region optimal one.     

The accelerated overrelaxation quadrant interlocking iterative method

In this paper we use a new splitting of the matrix A of the linear system A x = b introduced in [1] and we present a new version of the AOR method, more suitable for parallel processing, which involves explicit evaluation of 2 × 2 blocks.

We also obtain several convergence conditions for this new method, when the matrix A of (1.1) belongs to different classes of matrices. Some results, given in [1], are also improved and generalised.     

Common fixed points of a countable family of multivalued quasi-nonexpansive mappings in uniformly convex Banach spaces

In this paper, we introduce a one-step iterative scheme for finding a common fixed point of a countable family of multivalued quasi-nonexpansive mappings in a real uniformly convex Banach space. We establish weak and strong convergence theorems of the proposed iterative scheme under some control conditions.     

A higher order method for multiple zeros of nonlinear functions

A method of order three for finding multiple zeros of nonlinear functions is developed. The method requires two evaluations of the function and one evaluation of the derivative per step.     

A numerical algorithm for image sequence inpainting that preserves fine textures

We describe a fast, reliable and automatic algorithm for image sequence inpainting that combines spatio-temporal interpolation with fine texture preservation inside missing areas. The algorithm provides an estimate of the inpainting error by using an automatic geometric recognition of missing regions. Computational kernels are sparse linear systems solved using Generalized Minimum RESidual iterative method equipped with AMG multigrid preconditioner. Experiments on synthetic and real data are discussed.     

A third-order convergent iterative method for solving non-linear equations

In this paper, we present and analyse a new predictor-corrector iterative method for solving non-linear single variable equations. The convergence analysis establishes that the new method is cubically convergent. Numerical tests show that the method is comparable with the well-known existing methods and in many cases gives better results.     

A Genetic‐Based Iterative Quantile Regression Algorithm for Analyzing Fatigue Curves

Accurate prediction of fatigue failure times of materials such as fracture and plastic deformation at various stress ranges has a strong bearing on practical fatigue design of materials. In this study, we propose a novel genetic‐based iterative quantile regression (GA‐IQR) algorithm for analyzing fatigue curves that represent a nonlinear relationship between a given stress amplitude and fatigue life. We reduce the problem to a linear framework and develop the iterative algorithm for determining the model coefficients including unknown fatigue limits. The procedure keeps updating the estimates in a direction to reduce its resulting error. Also, our approach benefits from the population‐based stochastic search of the genetic algorithms so that the algorithm becomes less sensitive to its initialization. Compared with conventional approaches, the proposed GA‐IQR requires fewer assumptions to develop fatigue model, capable of exploring the data structure in a relatively flexible manner. All procedures and calculations are quite straightforward, such that the proposed quantile regression model has a high potential value in a wide range of applications for exploring nonlinear relationships with lifetime data. Computational results for real data sets found in the literature present good evidences to support the argument. Copyright © 2012 John Wiley & Sons, Ltd.     

种植屋面用耐根穿刺防水涂料检测技术研究

从应用性能和耐根穿刺性能两方面研究了耐根穿刺防水涂料的检测技术:应用性能方面除耐霉菌性能外,还根据防水涂料分层多次涂刷或喷涂、可连续施工的特点,制定了涂层间剥离强度试验方法;耐根穿刺性能检测方法研究中,新增了潮湿层的种类,重点介绍了内衬箱的制作方法,从内衬箱选材和构造、涂层厚度和质量多个方面进行控制,确保种植箱制备成功。通过该研究,完善了耐根穿刺防水涂料性能的检测方法,为各检验机构和生产企业开展耐根穿刺防水涂料性能检测提供参考。     

焊剂带约束电弧超窄间隙焊接根焊方法

超窄间隙焊接在对接焊接中有着独特的优势.在实际焊接工程中,对接焊有时要求采用单面焊双面成型的方法进行根焊.采用焊剂带约束熔化极电弧超窄间隙焊接的方法,结合在工件背面衬垫焊剂,并用铜板对焊剂加以支撑的背面焊缝强制成型方法进行熔化极电弧根焊试验.结果表明,通过焊剂带约束熔化极电弧,选择合适的焊接电压、焊接电流可以使坡口根部...