考虑基本变量模糊与随机性的广义自适应重要抽样法

基于模糊随机广义可靠性分析向随机可靠性分析的转换,提出了模糊随机广义失效概率计算的自适应重要抽样法,该方法利用模拟退火智能优化,在模拟的过程中逐步逼近模糊随机广义设计点,并在模拟过程中自适应地构造重要抽样函数,从而使得模糊随机失效概率的计算效率和精度大为提高。与传统的重要抽样法相比,本文方法无需首先求解失效模式的设计点。对非线性失效区和复杂等价概率密度函数,由于模拟退火智能优化在寻找设计点时比诸如一次二阶矩法(FOSM)更为有效,因而所提方法适合非线性失效区和复杂等价概率密度函数情况下的广义可靠性分析。另外,随着重要抽样密度函数逐步向最优值的自动调整,抽取的样本数逐渐增大,使后续构建的重要抽样函数更能体现对广义失效概率贡献的重要程度,并使失效概率的计算更加准确。文中算例证明了所提方法的合理性。     

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Studies on the workability of precise seeders by means of labelling methods has been possible due to the solution of the following problems: labelling of seeds, radiation collimation of labelled seeds being sown, elaboration of measuring and registering systems as well as processing systems of a measuring signal. The developed method allows for precise, quick and fully objective evaluation of the studied seeders to be done under natural conditions.     

Optimal Randomness for Stochastic Configuration Network (SCN) with Heavy-Tailed Distributions

Stochastic Configuration Network (SCN) has a powerful capability for regression and classification analysis. Traditionally, it is quite challenging to correctly determine an appropriate architecture for a neural network so that the trained model can achieve excellent performance for both learning and generalization. Compared with the known randomized learning algorithms for single hidden layer feed-forward neural networks, such as Randomized Radial Basis Function (RBF) Networks and Random Vector Functional-link (RVFL), the SCN randomly assigns the input weights and biases of the hidden nodes in a supervisory mechanism. Since the parameters in the hidden layers are randomly generated in uniform distribution, hypothetically, there is optimal randomness. Heavy-tailed distribution has shown optimal randomness in an unknown environment for finding some targets. Therefore, in this research, the authors used heavy-tailed distributions to randomly initialize weights and biases to see if the new SCN models can achieve better performance than the original SCN. Heavy-tailed distributions, such as Lévy distribution, Cauchy distribution, and Weibull distribution, have been used. Since some mixed distributions show heavy-tailed properties, the mixed Gaussian and Laplace distributions were also studied in this research work. Experimental results showed improved performance for SCN with heavy-tailed distributions. For the regression model, SCN-Lévy, SCN-Mixture, SCN-Cauchy, and SCN-Weibull used less hidden nodes to achieve similar performance with SCN. For the classification model, SCN-Mixture, SCN-Lévy, and SCN-Cauchy have higher test accuracy of 91.5%, 91.7% and 92.4%, respectively. Both are higher than the test accuracy of the original SCN.     

Selecting an Effective Entropy Estimator for Short Sequences of Bits and Bytes with Maximum Entropy

Entropy makes it possible to measure the uncertainty about an information source from the distribution of its output symbols. It is known that the maximum Shannon’s entropy of a discrete source of information is reached when its symbols follow a Uniform distribution. In cryptography, these sources have great applications since they allow for the highest security standards to be reached. In this work, the most effective estimator is selected to estimate entropy in short samples of bytes and bits with maximum entropy. For this, 18 estimators were compared. Results concerning the comparisons published in the literature between these estimators are discussed. The most suitable estimator is determined experimentally, based on its bias, the mean square error short samples of bytes and bits.     

Rat pups and random robots generate similar self‐organized and intentional behavior

Biorobotic research continually demonstrates that behavior and cognition can be the emergent products of (1) embodied agents that are (2) dynamically embedded within an environment and (3) equipped with simple sensorimotor rules. Thigmotaxis is an orientation response to contact manifested in infant rats by wall following, corner burrowing, and group aggregation. Orientation responses have been long thought to be mediated only by sensory or central processes. Here we show that a random control architecture in a morphologically similar robot embedded in a scaled environment can reproduce thigmotaxic behaviors seen in infant rats. We conclude that (1) and (2) may play a larger role than previously thought in the generation of complex behaviors. © 2006 Wiley Periodicals, Inc. Complexity 12: 53–66, 2006     

C0复杂度的数学基础

对于许多同时具有强烈非线性和非平稳性的连续生物医学信号来说，计算其复杂度往往要求：1）在数据长度比较短的情况下也可以得出比较鲁棒的估计值；2）无需对原始信号作像二值化这样的过分的粗粒化，我们以前所提出的C0复杂度就是这样的一种度量，但是这种度量缺乏严格的数学基础，因而影响到它的应用，提出了一种改进形式，并严格证明了它的重要性质。从而表明这个量在一定条件下可以作为时间序列随机程度的指标，因而在随机性复杂度的意义下也可作为复杂性的一个定量指标，由于这个量有计算速度快的优点，因此特别适合于一些需要大量计算复杂度的场合，例如计算长时间过程中滑动窗口中复杂度的动态变化。     

Correlated randomness: Some examples of exotic statistical physics

One challenge of biology, medicine, and economics is that the systems treated by these sciences have no perfect metronome in time and no perfect spatial architecture-crystalline or otherwise. Nonetheless, as if by magic, out of nothing but randomness one finds remarkably fine-tuned processes in time and remarkably fine-tuned structures in space. To understand this ‘miracle’, one might consider placing aside the human tendency to see the universe as a machine. Instead, one might address the challenge of uncovering how, through randomness (albeit, as we shall see, strongly correlated randomness), one can arrive at many spatial and temporal patterns in biology, medicine, and economics. Inspired by principles developed by statistical physics over the past 50 years-scale invariance and universality-we review some recent applications of correlated randomness to fields that might startle Boltzmann if he were alive today.     

Simple Constructions of Almost k-wise Independent Random Variables

We present three alternative simple constructions of small probability spaces on n bits for which any k bits are almost independent. The number of bits used to specify a point in the sample space is (2 + o(1)) (log log n + k/2 + log k + log 1/?), where ? is the statistical difference between the distribution induced on any k bit locations and the uniform distribution. This is asymptotically comparable to the construction recently presented by Naor and Naor (our size bound is better as long as ? < 1/(k log n)). An additional advantage of our constructions is their simplicity.     

STUDY ON POLYSULFONE-POLYESTER BLOCK COPOLYMERS

Synthesis and characterization of a series of Polysulfone (PSF)-Polyester (PEs) block copolymers were studied.The degree of randomness (B) of these block eopolymers was calculated from the intensities of their proton signals in ~1H NMR spectra and lies in the region of 0randomness (B) and the average sequence length (L) in block copolymers were relatively dependent on the reaction conditions, various feed ratios and structure of diols.The phenomenon was observed, when the PSF-PEs block copolymers dissolved in different solvents they had different viscosities and molecular conformations.The PSF-PEs block copolymers had better solvent resistance than homo-polysulfone.     

随机利率下的风险模型

考虑随机利率情形下关于风险损失(或赔款)的随机风险模型.当随机利率取一般的独立增量过程时,得到了总索赔额精算现值的各阶矩.特别地,当独立增量过程为Wiener过程,损失分布为Pareto分布的情形下,给出了总索赔额精算现值各阶矩的具体表达式.