EXPONENTIAL STABILITY AND PERIODIC SOLUTION OF HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH DISCRETE DELAYS

In this paper, we study the existence, uniqueness, and the global exponential stability of the periodic solution and equilibrium of hybrid bidirectional associative memory neural networks with discrete delays. By ingeniously importing real parameters di > 0 (i = 1,2, …, n) which can be adjusted, making use of the Lyapunov functional method and some analysis techniques, some new sufficient conditions are established. Our results generalize and improve the related results in [9]. These conditions can be used both to design globally exponentially stable and periodical oscillatory hybrid bidirectional associative neural networks with discrete delays, and to enlarge the area of designing neural networks. Our work has important significance in related theory and its application.     

Fuzzy Entropy： Axiomatic Definition and Neural Networks Model

The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model.     

A new algorithm for fixed design regression and denoising

In this paper, we present a new algorithm to estimate a regression function in a fixed design regression model, by piecewise (standard and trigonometric) polynomials computed with an automatic choice of the knots of the subdivision and of the degrees of the polynomials on each sub-interval. First we give the theoretical background underlying the method: the theoretical performances of our penalized least-squares estimator are based on non-asymptotic evaluations of a mean-square type risk. Then we explain how the algorithm is built and possibly accelerated (to face the case when the number of observations is great), how the penalty term is chosen and why it contains some constants requiring an empirical calibration. Lastly, a comparison with some well-known or recent wavelet methods is made: this brings out that our algorithm behaves in a very competitive way in term of denoising and of compression.     

中子俘获瞬发γ射线数据评价(英文)

简要地介绍了中子俘获瞬发γ射线数据及其衰变纲图的评价方法技术、主要程序及其功能、数据评价流程、强度平衡检验，以及对A=1-44的稳定核素和A>190的部分稳定核素的热中子俘获瞬发γ射线数据及其衰变纲图评价的具体应用.The method of prompt γ-ray data evaluation for neutron capture and how to calculate the prompt γ-ray intensities of neutron capture have been briefly presented. The prompt γ-ray data of thermal-neutron capture of some stable nuclei for A=1-44 and A>190 have been evaluated. The ENSDF format has been adopted. The checks of intensity balance and format have been made. The examples are given to illustrate its application.     

A class of multivariate skew-normal models

The existing model for multivariate skew normal data does not cohere with the joint distribution of a random sample from a univariate skew normal distribution. This incoherence causes awkward interpretation for data analysis in practice, especially in the development of the sampling distribution theory. In this paper, we propose a refined model that is coherent with the joint distribution of the univariate skew normal random sample, for multivariate skew normal data. The proposed model extends and strengthens the multivariate skew model described in Azzalini (1985,Scandinavian Journal of Statistics,12, 171–178). We present a stochastic representation for the newly proposed model, and discuss a bivariate setting, which confirms that the newly proposed model is more plausible than the one given by Azzalini and Dalla Valle (1996,Biometrika,83, 715–726).     

Hydrogel‐like elastic membrane consisting of semi‐interpenetrating polymer networks based on a phosphorylcholine polymer and a segmented polyurethane

To obtain a hydrogel‐like elastic membrane, we prepared semi‐interpenetrating polymer networks (IPNs) by the radical polymerization of methacrylates such as 2‐methacryloyloxyethyl phosphorylcholine (MPC), 2‐hydroxyethylmethacrylate, and triethyleneglycol dimethacrylate diffused into segmented polyurethane (SPU) membranes swollen with a monomer mixture. The values of Young's modulus for the hydrated semi‐IPN membranes were less than that for an SPU membrane because of higher hydration, but they were much higher than that for a hydrated MPC polymer gel (non‐SPU). According to a thermal analysis, the MPC polymer influenced the segment association of SPU. The diffusion coefficient of 8‐anilino‐1‐naphthalenesulfonic acid sodium salt from the semi‐IPN membrane could be controlled with different MPC unit concentrations in the membrane, and it was about 7 × 10² times higher than that of the SPU membrane. Fibroblast cell adhesion on the semi‐IPN membrane was effectively reduced by the MPC units. We concluded that semi‐IPNs composed of the MPC polymer and SPU may be novel polymer materials possessing attractive mechanical, diffusive‐release, and nonbiofouling properties. © 2002 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 68–75, 2003     

Rate of Convergence of a Stochastic Particle System for the Smoluchowski Coagulation Equation

By continuing the probabilistic approach of Deaconu et al. (2001), we derive a stochastic particle approximation for the Smoluchowski coagulation equations. A convergence result for this model is obtained. Under quite stringent hypothesis we obtain a central limit theorem associated with our convergence. In spite of these restrictive technical assumptions, the rate of convergence result is interesting because it is the first obtained in this direction and seems to hold numerically under weaker hypothesis. This result answers a question closely connected to the Open Problem 16 formulated by Aldous (1999).     

Tail probabilities of the limiting null distributions of the Anderson–Stephens statistics

For the purpose of testing the spherical uniformity based on i.i.d. directional data (unit vectors) z_i, i=1,…,n, Anderson and Stephens (Biometrika 59 (1972) 613–621) proposed testing procedures based on the statistics S_max=max_u S(u) and S_min=min_u S(u), where u is a unit vector and nS(u) is the sum of squares of u′z_i's. In this paper, we also consider another test statistic S_range=S_max−S_min. We provide formulas for the P-values of S_max, S_min, S_range by approximating tail probabilities of the limiting null distributions by means of the tube method, an integral-geometric approach for evaluating tail probability of the maximum of a Gaussian random field. Monte Carlo simulations for examining the accuracy of the approximation and for the power comparison of the statistics are given.     

线性规划的符号跟踪算法

分析了只含一个约束条件的线性规划最优基变量的特征，将其运用到搜寻含m个约束条件的线性规划的最优基变量，从而提出了线性规划的符号跟踪算法，为线性规划求解提供了新途径。