Eigenvalue approach to study the effect of rotation and relaxation time in generalized magneto-thermo-viscoelastic medium in one dimension

The fundamental equations of the problems of generalized thermoelasticity with one relaxation parameter including heat sources in infinite rotating magneto-thermo-viscoelastic media have been derived in the form of a vector matrix differential equation in the Laplace transform domain for a one dimensional problem. These equations have been solved by the eigenvalue approach to determine deformations, stress, and temperature. The results have been compared to those available in the existing literature. The graphs have been drawn to show the effect of rotation in the medium.     

关于微分熵的一类强偏差定理

利用关于乘积分布密度的相对熵和相对熵率的概念,建立了相依连续型随机变量序列关于参考微分熵的一类强偏差定理,证明中给出了将Laplace变换应用于微分熵强偏差定理的研究的一种途径．     

On Hardy’s Theorem on SU(1, 1)

The classical Hardy theorem asserts that ■ and its Fourier transform ■ can not both be very rapidly decreasing.This theorem was generalized on Lie groups and also for the Fourier-Jacobi transform.However,on SU(1,1)there are infinitely many"good"functions in the sense that ■ and its spherical Fourier transform ■ both have good decay. In this paper,we shall characterize such functions on SU(1,1).     

基于移动Agent技术的医学图像检索方法

针对现有医学图像检索方法中，检索算法速度较慢、准确性较低以及远程检索时占用大量带宽等问题，设计并实现了一种基于移动Agent技术的医学图像检索方法，重点讨论了该方法实现的关键技术，包括提升框架下的M带整数小波变换和提取多通道纹理特征的检索算法．模拟实验结果表明，该方法实时性较强，占用网络带宽较少，采用的算法运算速度提高近10倍、运算复杂度降低约50％，提取的纹理特征能充分表达图像内容，较好地满足了医学图像的检索要求，实现了对医学图像库快速较准确的检索．     

On the number of full levels in tries

We study the asymptotic distribution of the fill‐up level in a binary trie built over n independent strings generated by a biased memoryless source. The fill‐up level is the number of full levels in a tree. A level is full if it contains the maximum allowable number of nodes (e.g., in a binary tree level k can have up to 2^k nodes). The fill‐up level finds many interesting applications, e.g., in the internet IP lookup problem and in the analysis of level compressed tries (LC tries). In this paper, we present a complete asymptotic characterization of the fill‐up distribution. In particular, we prove that this distribution concentrates on one or two points around the most probably value k = ?log_1/qn ? log log log n + 1 + log log(p/q)?, where p > q = 1 ? p is the probability of generating the more likely symbol (while q = 1 ? p is the probability of the less likely symbol). We derive our results by analytic methods such as generating functions, Mellin transform, the saddle point method, and analytic depoissonization. We also present some numerical verification of our results. © 2004 Wiley Periodicals, Inc. Random Struct. Alg., 2004     

代数课程教学改革的一些探索

本文结合代数教学中的实际情况．针对代数教学过程中出现的问题。提出了在代数教学过程中改进教学方法的几条措施．     

Consolidation around a borehole embedded in media with double porosity under release of geostatic stresses

The paper deals with the stress, displacement, pore and fissure pressures fields induced by the drilling and/or the pressurization of a vertical borehole in a formation of water-saturated porous media with double porosity. The solution includes the boundary condition of non-hydrostatic in situ state of stress. The solid skeleton is assumed to behave as a linearly poroelastic material with compressible constituents. The analytical solution is derived in Laplace’s space and transformed to the time domain using a numerical inversion technique. The histories of pore and fissure pressures are illustrated to show the influence of permeabilities of the pore and fissure systems.     

Improved holographic particle sizing by using absolute values of the wavelet transform

A new method for sizing particle from in-line particle holograms by using absolute values of the wavelet transform is proposed in order to improve accuracy in measurements. The proposed method provides direct calculation of the particle size by using spatial frequency information of a chirp signal at minima position of an envelope function. Simulation and experimental results are presented.     

Widrow-cellular neural network and optoelectronic implementation

A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination.