ρ＊-混合序列加权和的完全收敛性

讨论了ρ*-混合序列加权和的完全收敛性,将文[8]中的定理3推广至ρ*-混合序列的情形且加强了文[8]中的定理3的结论.将文[9]中的定理推广至ρ*-混合序列的情形.

不同分布ρ~*-混合序列的完全收敛性

本文通过讨论随机变量矩的存在性和随机变量序列尾概率级数收敛性之间的关系,在一定的混合速度下,给出了ρ-混合序列部分和更为一般的完全收敛性.

ρ^＊-混合随机变量序列的强大数定理

利用随机变量的截尾方法和Háyek-Rényi型最大值不等式研究了ρ*-混合随机变量序列.在一定的条件下,得到了ρ*-混合随机变量序列的强大数定理.

log-最优投资组合的极限定理

本文研究了* -混合股票市场以及没有约束条件下股票市场的log-最优投资组合问题,利用强极限定理的证明方法,得到了关于长期连续投资log-最优投资组合的极限性质.

Prediction of Gas Emission Based on Infor-mation Fusion and Chaotic Time Series

In order to make more exact predictions of gas emissions, information fusion and chaos time series are com- bined to predict the amount of gas emission in pits. First, a multi-sensor information fusion frame is established. The frame includes a data level, a character level and a decision level. Functions at every level are interpreted in detail in this paper. Then, the process of information fusion for gas emission is introduced. On the basis of those data processed at the data and character levels, the chaos time series and neural network are combined to predict the amount of gas emission at the decision level. The weights of the neural network are gained by training not by manual setting, in order to avoid subjectivity introduced by human intervention. Finally, the experimental results were analyzed in Matlab 6.0 and prove that the method is more accurate in the prediction of the amount of gas emission than the traditional method.

On the Second Borel-Cantelli Lemma for α-mixing Sequences of Events

In this paper, we give some conditions on diverging rate of series of the probabilities and converging rate of series of the α-mixing coefficients for sequences of events, under which the conclusion of the Second Borel-Cantelli Lemma holds. As corollaries, some moment conditions are obtained, under which the strong law of large numbers holds for sequences of identically distributed random variables.

Linear Growth of Continuous-Wave Four-Wave Mixing with Dual Induced Transparency

Using Schroedinger-Maxwell formalism, we propose and analyze an opticalfour-wave mixing (FWM) scheme for the generation of coherent light in a coherent six-level atomicmedium based on dual electromagnetically induced transparency (EIT). We show that the significantlyenhanced conversion efficiency enabled by ultraslow propagation of pump waves has no directrelationship with the single-photon detuning, which is different from the FWM with a single EIT. Themost important feature is that our scheme is also capable of inhibiting and delaying the onset ofthe detrimental three-photon destructive interference that looks like a recent scheme [Phys. Rev.Lett. 91 (2003) 243902] and may be used for generating short-wave-length coherent radiation.

独立加权和的完全收敛性

Stout在文献[1]中留下如下一个问题:在文献[1]定理4.1.5的条件下已推出a.s.收敛的结果,问能否推出完全收敛的结果?该文对此问题作了圆满的回答,并加强和推广了文献[1]中定理4.1.5的结论.

A new hybrid algorithm for global optimization and slope stability evaluation

A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm （GSA） with the sequential quadratic programming （SQP）, namely GSA-SQP, for solving global optimization problems and minimization of factor of safety in slope stability analysis. The new algorithm combines the global exploration ability of the GSA to converge rapidly to a near optimum solution. In addition, it uses the accurate local exploitation ability of the SQP to accelerate the search process and find an accurate solution. A set of five well-known benchmark optimization problems was used to validate the performance of the GSA-SQP as a global optimization algorithm and facilitate comparison with the classical GSA. In addition, the effectiveness of the proposed method for slope stability analysis was investigated using three ease studies of slope stability problems from the literature. The factor of safety of earth slopes was evaluated using the Morgenstern-Price method. The numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions and slope stability problems.

Extreme value distributions of mixing two sequences with different MDA＇s

Suppose {Xi, i≥1} and {Yi, i≥1} are two independent sequences with distribution functions FX(x) and FY(x), respectively. Zi is the combination of Xi and Yi with a probability pn for each i with 1≤i≤n. The extreme value distribution ,n GZ(x) of this particular triangular array of the i.i.d. random variables Z1, , Z2, ,…, Zn n n ,nis discussed. We found a new form of the extreme value distribution ΛA(ρx)Λ(x)(0<ρ <1), which is not max-stable. It occurs if FX(x) and FY(x) belong to the same MDA(Λ). GZ(x) does not exist as mixture forms of the different types of extreme value distributions.

Moving object detection method based on complementary multi resolution background models

A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models were used.The ghost and real static object could be classified by comparing the similarity of the edge images further.In each group,the multi resolution Gaussian mixture models were used and dual thresholds were applied in every resolution in order to get a complete object mask without much noise.The computational color model was also used to depress illustration variations and light shadows.The proposed method was verified by the public test sequences provided by the IEEE Change Detection Workshop and compared with three state-of-the-art methods.Experimental results demonstrate that the proposed method is better than others for all of the evaluation parameters in intermittent object motion sequences.Four and two in the seven evaluation parameters are better than the others in thermal and dynamic background sequences,respectively.The proposed method shows a relatively good performance,especially for the intermittent object motion sequences.

Charaterization of Citrus Hybrid ＂Huangguogan＂ through the Combination of Morphological and Molecular Markers

Huangguogan, an obvious Citrus hybrid, is suitable for transportation and export and ripens in March or April. Because of late season, it may playa significant role in fruit market. However, its origin is still unconfirmed. The aim of this study was to clarify the possible parentage of Huangguogan via the combination of morphological and molecular markers including simple sequence repeat （SSR） and chloroplast simple sequence repeat （cpSSR）. Analysis of morphological traits including leaf stalk length, phylliform index and fruit shape index indicated that Huangguogan had similarities in morphology with Sweet orange. The SSR Cluster Analysis showed that Huangguogan was clustered together with Hongju tangerine and revealed -80% genetic similarity. They illustrated a close genetic distance between Huangguogan and Hongju tangerine. In addition, the bands of2 polymorphic cpSSR were identical in Huangguoggan and Sweet orange. Consequently, it is likely that its female parentage was the sweet orange （Citrus sinensis （L.） Osbeck） and its male parentage was the tangerine （Citrus reticulata Blanco）.

Introducing semantic information into motion graph

To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.

Fast garment simulation with aid of hybrid bones

A data-driven method was proposed to realistically animate garments on human poses in reduced space. Firstly, a gradient based method was extended to generate motion sequences and garments were simulated on the sequences as our training data. Based on the examples, the proposed method can fast output realistic garments on new poses. Our framework can be mainly divided into offline phase and online phase. During the offline phase, based on linear blend skinning(LBS), rigid bones and flex bones were estimated for human bodies and garments, respectively. Then, rigid bone weight maps on garment vertices were learned from examples. In the online phase, new human poses were treated as input to estimate rigid bone transformations. Then, both rigid bones and flex bones were used to drive garments to fit the new poses. Finally, a novel formulation was also proposed to efficiently deal with garment-body penetration. Experiments manifest that our method is fast and accurate. The intersection artifacts are fast removed and final garment results are quite realistic.

Research on natural language recognition algorithm based on sample entropy

Sample entropy can reflect the change of level of new information in signal sequence as well as the size of the new information. Based on the sample entropy as the features of speech classification, the paper firstly extract the sample entropy of mixed signal, mean and variance to calculate each signal sample entropy, finally uses the K mean clustering to recognize. The simulation results show that： the recognition rate can be increased to 89.2% based on sample entropy.

Strong approximation for ρ-mixing sequences

We establish strong invariance principles for sums of stationary p-mixing random variables with finite and infinite second moments under weaker mixing rates. Some earlier results are improved. As applications, some results of the law of the iterated logarithm with finite and infinite variance are obtained, also a conjecture raised by Shao in 1993 is solved

LARGE DEVIATIONS FOR STATIONARY Φ-MIXING SEQUENCES IN τ-TOPOLOGY

The results of Bryc on large deviations for empirical measures of stationary Φ-mixing sequences are extended. Bryc states his results in the usual weak topology on the space ofprobability measures. In this paper, under somewhat weaker assumptions than those of Bryc,the author extends Bryc's results by taking the finer topology which is generated by the integralsover bounded measurable functions.

In-situ measurement of atmospheric CFC-11 at the Shangdianzi Global Atmosphere Watch(GAW) Regional Station

An in-situ GC-ECD system was used to measure halocarbons at Shangdianzi （SDZ） GAW regional station. In this paper, we reported observational results of atmospheric CFC- 11 （CCI3F） mixing ratios from April 2007 to March 2008. The CFC- 11 time series showed large variability. Approximately 62% observed values were filtered as non-background data. The median, 10% and 90% percentiles of CFC-11 background mixing ratios were 245.4 ppt （10-12 mol/mol）, 244.6 ppt and 246.1 ppt, respectively; whereas those of non-background CFC- 11 mixing ratios were 254.7, 246.6 and 272.1 ppt, respectively. Significant differences in background and non-background CFC-11 mixing ratios were observed between summer and autumn, mainly because of the CFC-11 stored in loam being prone to atmospheric release in hot seasons. Comparison of tile SDZ data with the five AGAGE stations suggested agreement with mid-high latitude Northern Hemisphere stations MHD, THD and RPB. The SDZ data were higher than that of Southern Hemisphere stations CGO and SMO. Higher CFC-11 mixing ratios measured in different seasons were always associated with winds from the W-WSW-SW sector, indicating that the airflow coming from this wind sector has a positive contribution to CFC- 11 concentrations. The CFC-11 mixing ratios were higher in autumn and summer than in spring and winter, in which its mixing ratios were very close to the atmospheric background level. This was happened especially when airflow originated from the NNE-NE-ENE-E sector, indicating the air masses coming from these wind directions was relatively clean.

Restricted normal mixture QMLE for non-stationary TGARCH(1,1) models

The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the estimation of non-stationary first order TGARCH models.Restricted normal mixture quasi-maximum likelihood estimation(NM-QMLE)for non-stationary TGARCH models is proposed in the sense that we estimate the other parameters with any fixed location parameter.We show that the proposed estimators(except location parameter)are consistent and asymptotically normal under mild regular conditions.The impact of relative leptokursis and skewness of the innovations’distribution and quasi-likelihood distributions on the asymptotic efficiency has been discussed.Numerical results lend further support to our theoretical results.Finally,an illustrated real example is presented.

Moment Bounds for Strong Mixing Sequences and Their Application

Some moment inequalities for the strong mixing random variable sequence are established, and applied to discuss the asymptotic normality of the general weight function estimate for the fixed design regression model.