基于邻域统计特性的概率神经网络及其在自动目标识别中的应用

在概率神经的一种改进模型－ＦＤＯ网络的基础上，提出在设计网络收敛域时进一步考虑每一像素点周围８邻域的影响，对网络的作用函数加以修，使改进后的网络具有稳定性好且收敛速度快的优点。通过实验对改进前后网络的识别性能加以比较，证明改进后的网络特别适用于噪声图像的识别。     

拉盖尔-高斯光束通过有硬边光阑光学系统的传输

采用将硬边光阑展为有限个复高斯函数之和的方法,得到了拉盖尔-高斯光束通过有硬边光阑近轴ABCD光学系统中传输的近似解析公式,作了数值计算以说明传输公式的应用,并对使用该式的误差作了讨论。     

梯度折射率棒中传播的高斯光束轨迹解析解及其存在条件的讨论

本文提出光束轨迹方程的一般解，导出解析解的存在条件，推广了文献［１］的光线传播理论，文中以一特定梯度折射率棒为例，讨论了高斯光束在棒中的传播特性。     

Non-parametric empirical Bayes procedure

In this paper we introduce an empirical Bayes procedure for estimating an unknown parameter, say θ. This procedure gives the empirical Bayes estimator for θ and its associated minimum posterior risk in closed forms without estimating the unknown prior density function of θ. In such procedure the posterior probability density function of θ is not required. A sufficient statistic for θ with conditional probability density function in the one parameter exponential family is required. Instead of estimating the unknown prior density function, the marginal density function of the sufficient statistic must be estimated. As special cases the empirical Bayes estimators and their respective minimum posterior risks of the failure rate for the exponential distribution, the unknown scale parameters of Weibull and gamma distributions are obtained in simple forms as special cases. Numerical results and a simulation study are introduced to (i) investigate how the number of available past experiments and the sample size of each influence the accuracy of the empirical Bayes estimator, (ii) make a comparison between the presented procedure and the Bayes procedure when the prior probability density function of the parameter θ is gamma.     

Distributed Speech Recognition Systems and Some Key Factors Affecting It''''s Performance

1　IntroductionWiththerapiddevelopmentofInternetandmobilecommunications,theresearchonwirelessmobilenetworkshasbecomethenewhotspotinin formationtechnologyfield .Asweknow ,mobileterminals (mobilephone,forexample)arethetooltohelppeopletoaccessanyinformationtheyneedbyanymediaatanytimeandanywhere .However,itissometimesdifficultformobileterminalstoplaysucharolebecauseofthelimitationssuchaslimitedca pacity ,lowpower,andinconvenienceinoperating .So,peoplehopetofindanotherwaytoaccessnet workinformatio…     

Simulation-based sequential analysis of Markov switching stochastic volatility models

We propose a simulation-based algorithm for inference in stochastic volatility models with possible regime switching in which the regime state is governed by a first-order Markov process. Using auxiliary particle filters we developed a strategy to sequentially learn about states and parameters of the model. The methodology is tested against a synthetic time series and validated with a real financial time series: the IBOVESPA stock index (São Paulo Stock Exchange).     

Parametric circles and spheres

Formulations for parametric circles and spheres in terms of rational Gaussian (RaG) curves and surfaces are introduced. With the proposed formulations, a full circle is generated by interpolating a closed RaG curve to the vertices of an equilateral triangle, and a full sphere is generated by interpolating a closed RaG surface to the vertices of an octahedron with equilateral triangular faces. Generation of circles and spheres in this manner is very intuitive and easy to remember as the weights are all 1 and the nodes are all unique and uniformly spaced.     

Data decomposition using independent component analysis with prior constraints

In many data analysis problems, it is useful to consider the data as generated from a set of unknown (latent) generators or sources. The observations we make of a system are then taken to be related to these sources through some unknown function. Furthermore, the (unknown) number of underlying latent sources may be less than the number of observations. Recent developments in independent component analysis (ICA) have shown that, in the case where the unknown function linking sources to observations is linear, such data decomposition may be achieved in a mathematically elegant manner. In this paper, we extend the general ICA paradigm to include a very flexible source model, prior constraints and conditioning on sets of intermediate variables so that ICA forms one part of a hierarchical system. We show that such an approach allows for efficient discovery of hidden representation in data and for unsupervised data partitioning.     

二维轴对称折迭－组合腔CO2激光器失调时的输出光束的近场分析

给出平凹谐振腔和凹平凹谐振腔失调时光轴确定方法。在二维轴对称折迭－组合腔 激光器小角度失调运行时，对非相干并和和相干并和后的输出光束的近场强度分布做了分析和模拟。结果表明：小角度失调对4cm以内的近场影响不大，光强分布仍具有高斯状分布；对4cm以外的近场影响较大，光强分布发生相应的形变，且随着失调角度变大而变大。     

Existence of discrete-time LQG-controllers

Existence results for the LQG-controller are investigated. An infimal Riccati equation based controller may potentially give closed loop eigenvalues on the unit circle. Assuming left and right invertibility it is shown that there exists an optimal controller if and only if the Riccati equation based controller stabilizes the closed loop system after removal of all its unobservable and uncontrollable modes. Furthermore this reduced controller is the optimal controller, and its transfer function is unique. This existence condition is a considerable simplification of the more general geometric condition recently derived by Trentelman and Stoorvogel.