Parameter estimation in Bayesian reconstruction of SPECT images: An aid in nuclear medicine diagnosis

Despite the adequacy of Bayesian methods to reconstruct nuclear medicine SPECT (single‐photon emission computed tomography) images, they are rarely used in everyday medical practice. This is primarily because of their computational cost and the need to appropriately select the prior model hyperparameters. We propose a simple procedure for the estimation of these hyperparameters and the reconstruction of the original image and test the procedure on both synthetic and real SPECT images. The experimental results demonstrate that the proposed hyperparameter estimation method produces satisfactory reconstructions. Although we have used generalized Gaussian Markov random fields (GGMRF) as prior models, the proposed estimation method can be applied to any priors with convex potential and tractable partition function with respect to the scale hyperparameter. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 21–27, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20003     

An improvement of the EDI method in linear elastic fracture mechanics by means of an a posteriori error estimator in G

In this paper, an error estimator that quantifies the effect of the finite element discretization error on the computation of the stress intensity factor in linear elastic fracture mechanics is presented. In order to obtain the proposed estimator, a shape design sensitivity analysis (SDSA) is applied to the fracture mechanics problem. Following this approach, one of the most efficient post‐processing techniques for computing the strain energy release rate G, the well‐known EDI method, may be interpreted as a continuum method of the SDSA. The proposed error estimator is based on the recovery of the gradient fields and its reliability has been checked by means of numerical problems, yielding very good estimations of the true error. The new estimator remarkably improves the results given by a previous error estimator, which is based on a discrete analytical approach of SDSA. As a consequence, the combination of the new error estimator and the result given by the EDI method provides a much more accurate estimation of G. Copyright © 2003 John Wiley & Sons, Ltd.     

On error estimator and p‐adaptivity in the generalized finite element method

This paper addresses the issue of a p‐adaptive version of the generalized finite element method (GFEM). The technique adopted here is the equilibrated element residual method, but presented under the GFEM approach, i.e., by taking into account the typical nodal enrichment scheme of the method. Such scheme consists of multiplying the partition of unity functions by a set of enrichment functions. These functions, in the case of the element residual method are monomials, and can be used to build the polynomial space, one degree higher than the one of the solution, in which the error functions is approximated. Global and local measures are defined and used as error estimator and indicators, respectively. The error indicators, calculated on the element patches that surrounds each node, are used to control a refinement procedure. Numerical examples in plane elasticity are presented, outlining in particular the effectivity index of the error estimator proposed. Finally, the ‐adaptive procedure is described and its good performance is illustrated by the last numerical example. Copyright © 2004 John Wiley & Sons, Ltd.     

多尺度鲁棒滤波技术

分析了小波变换消除白噪声的原理,验证了非白噪声情况下,这一方法不甚理想。为了提供一种有效实用的多尺度鲁棒滤波方法,结合鲁棒统计学的知识,研究一种鲁棒小波变换,可以抑制服从污染分布的干扰。研究表明,这种方法既有较强的鲁棒性又有较高的效率。     

Parameter Estimation of Time-Varying ARMA Model

The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedback linear estimation algorithm is used to estimate the time-varying parameters of the ARMA model. This algorithm includes 2 linear least squares estimations and a linear filter. The influence of the order of basis time-varying functions on parameters estimation is analyzed. The method has the advantage of simple, saving computation time and storage space. Theoretical analysis and experimental results show the validity of this method.     

Improvement of Channel Estimation with 16QAM Modulation over Fading Channel for DS-CDMA

The application of low complexity and low order robust regression algorithm in channel estimation with 16QAM over fading channel for DS-CDMA is presented in this paper After initial channel estimation with classical methods, channel gains estimated are filtered by linear or conic regression algorithm within a given regression length Simulation results show that this method offers up to 0,3 dB gain in a DS-CDMA system. The length and order of regression algorithm are two key parameters, which affect the system performance significantly and the optimal values of which depend on the speed of mobile station. It is demonstrated that this improved method can track fading channel accurately and outperforms over classical methods substantially by selecting appropriate parameters of regression algorithm under a certain channel environment.     

按转子磁场定向的异步电机无速度传感器矢量控制系统

设计了一种新颖的无速度传感器的矢量控制系统.该系统采用转子磁场定向,实现磁链与转矩的解耦控制;利用PI自适应控制的原理,对转子磁链在q轴的分量采用比例积分自适应控制机制,获取速度信号,实现速度闭环控制.实验结果表明,该方法实用简单且具有比较良好的性能.     

基于矢量加权中值滤波的快速分层运动估计算法

针对分层运动估计的特点,提出了一种简单有效的快速算法.该算法在底层通过对当前块的空间相邻块的运动矢量进行矢量加权中值滤波来产生一个候选矢量,该候选矢量能够更准确地预测运动,并对上层运动估算中出错的矢量提供保护,减少了错误传播.在顶层进行匹配误差计算时采用修正累计绝对误差(SAD)准则,平滑了矢量场,并进一步提高了运动估计的准确性.仿真实验表明,此算法用很少的运算量获得了较好的性能.     

噪声对贝叶斯频谱估计精度的影响

研究了贝叶斯频谱估计的基本理论和基本方法 ,分别对无噪声和有噪声的简谐正弦信号进行了频谱估计。计算结果显示 :无噪声信号频率估计偏倚为零 ;当信号噪声系数S/N =1时 ,贝叶斯频率估计的偏倚与Jaynes的理论值一致     

基于人工鱼群算法的参数估计方法

利用人工鱼群算法的基本特性 ,提出了一种新的参数估计方法 ,并进行了仿真实验研究 .结果表明 ,具有良好的跟踪性能和实时性