基于小波分解和鉴别共同矢量的人耳识别

针对高维、小样本的情况下使用Fisher线形鉴别分析进行特征提取存在的病态奇异问题,提出一种新的特征提取方法,即先对人耳样本图像进行二维离散小波分解,再利用DCV算法对小波分解后的低频信息分量作进一步的降维处理。不仅克服了小样本问题,也解决了直接使用DCV算法对人耳图像降维所引起的计算量大和计算速度过慢的问题。实验证明,该方法具有较好的识别率,是一种有效的特征提取算法。     

基于Radon变换的抗旋转攻击零水印算法

针对大多数基于变换域的零水印算法无法抵抗几何攻击（RST变换）的缺陷,提出一种基于Radon变换的抗旋转攻击零水印算法。通过Radon变换检测算法对发生旋转几何攻击后的图像进行几何校正并提取水印。仿真实验结果证明,该算法可以获得良好的图像视觉效果,对旋转几何攻击及加噪、滤波、JPEG压缩、剪切攻击有较好的鲁棒性。     

基于混沌级联的语音频域实时加密系统

针对现有语音实时保密通信系统中系统空载密钥泄漏现象导致容易遭受基于自适应同步控制方法攻击的问题,采用混沌级联对语音频域进行实时加、解密。该方案实现零密钥泄漏,有效抵御了基于自适应同步控制方法的攻击。系统测试分析结果表明,该方案是有效、安全的,优于基于单组混沌系统对时域的加密方法。     

Meshless local Petrov-Galerkin method for continuously nonhomogeneous linear viscoelastic solids

A meshless method based on the local Petrov-Galerkin approach is proposed for the solution of quasi-static and transient dynamic problems in two-dimensional (2-D) nonhomogeneous linear viscoelastic media. A unit step function is used as the test functions in the local weak form. It is leading to local boundary integral equations (LBIEs) involving only a domain-integral in the case of transient dynamic problems. The correspondence principle is applied to such nonhomogeneous linear viscoelastic solids where relaxation moduli are separable in space and time variables. Then, the LBIEs are formulated for the Laplace-transformed viscoelastic problem. The analyzed domain is covered by small subdomains with a simple geometry such as circles in 2-D problems. The moving least squares (MLS) method is used for approximation of physical quantities in LBIEs.     

a尺度Haar小波基的构造

对伸缩因子a为大于1的正整数的Haar小波基进行了统一构造，并给出了分解和重构算法。指出只需对一实对称矩阵求特征向量，便容易得到相应的a-1个母小波。     

DWT－Based Watermarking Scheme for Digital Images

A watermarking scheme for digital images is introduced. This method is based on discrete wavelet transform and spread spectrum technique. A discrete wavelet transformed binary signature image is expanded by an m-sequence and added to the large wavelet coefficients of a host image with a scale factor. Good balance be-tween transparency and robustness is achieved by the selection of the scale factor. In addition, the spread spec-trum technique is adopted to increase the robustness of this watermarking scheme. The experimental results show that the proposed method is of good performance and robustness for common image operations such as JPEG lossy compression, etc.     

Numerical inversion of multidimensional Laplace transforms by the Laguerre method

Numerical transform inversion can be useful to solve stochastic models arising in the performance evaluation of telecommunications and computer systems. We contribute to this technique in this paper by extending our recently developed variant of the Laguerre method for numerically inverting Laplace transforms to multidimensional Laplace transforms. An important application of multidimensional inversion is to calculate time-dependent performance measures of stochastic systems. Key features of our new algorithm are: (1) an efficient FFT-based extension of our previously developed variant of the Fourierseries method to calculate the coefficients of the multidimensional Laguerre generating function, and (2) systematic methods for scaling to accelerate convergence of infinite series, using Wynn's ε-algorithm and exploiting geometric decay rates of Laguerre coefficients. These features greatly speed up the algorithm while controlling errors. We illustrate the effectiveness of our algorithm through numerical examples. For many problems, hundreds of function evaluations can be computed in just a few seconds.     

基于FRFT的线性调频信号映射方法的快速算法

针对基于分数傅立叶变换(Fractional Fourier transform，FRFT)的线性调频信号(LFM)的参数估计方法，提出了基于Radon变换的判决准则，并建立了相应的快速算法。该映射方法将具有同样调频斜率、同样多普勒中心频率、不同初始相位的信号映射到同一个点。该快速算法的计算量等同于FRFT的计算量，计算结果的精确度取决于连续两次的FRFT运算。     

The Conditional Probability Density Function for a Reflected Brownian Motion

Models in economics and other fields often require a restricted Brownian motion because frequently implicit or explicit barriers restrict the domain. This paper contributes to the literature on reflected Brownian motion by deriving its conditional density function as a closed-form expression that consists of infinite sums of Gaussian densities. This solution is compared with an alternative, trigonometric expression derived earlier. Numerical analyses reveal that convergence properties of the expression derived in this paper are superior to those of the alternative representation for most practically relevant set-ups. Despite the complex appearance of the density formula, its use only requires fractions of a second on simple desktop computers such that, next to the theoretical appeal, also practicability is guaranteed.     

On neuro-wavelet modeling

We survey a number of applications of the wavelet transform in time series prediction. The Haar à trous wavelet transform is proposed as a means of handling time series data when future data is unknown. Results are exemplified on financial futures and S&P500 data. Nonlinear and linear multiresolution autoregressionmodels are studied. Experimentally, we show that multiresolution approaches can outperform the traditional single resolution approach to modeling and prediction.