利用改进微分进化算法实现线性系统逼近

提出一种基于改进的微分进化算法的逼近算法。新算法通过参考粒子群算法惯性权重思想,引入惯性加权系数,在计算初期能够维持个体的多样性,后期能够加快算法的收敛速度,提高了DE算法的性能。最后对典型的稳定线性系统逼近问题进行了数值计算,计算结果证明该算法优于未改进微分进化算法,能够以更少的进化代数和更小的计算量找到高质量的逼近模型。     

A hierarchical fair service curve algorithm for link-sharing,real-time, and priority services

We study hierarchical resource management models and algorithms that support both link-sharing and guaranteed real-time services with priority (decoupled delay and bandwidth allocation). We extend the service curve based quality of service (QoS) model, which defines both delay and bandwidth requirements of a class in a hierarchy, to include fairness, which is important for the integration of real-time and hierarchical link-sharing services. The resulting fair service curve (FSC) link-sharing model formalizes the goals of link-sharing, real-time and priority services and exposes the fundamental trade-offs between these goals. In particular, with decoupled delay and bandwidth allocation, it is impossible to simultaneously provide guaranteed real-time service and achieve perfect link-sharing. We propose a novel scheduling algorithm called hierarchical fair service curve (H-FSC) that approximates the model closely and efficiently. The algorithm always guarantees the service curves of leaf classes, thus ensures real-time and priority services, while trying to minimize the discrepancy between the actual services provided to and the services defined by the FSC link-sharing model for the interior classes. We have implemented the H-FSC scheduler in NetBSD. By performing analyzes, simulations and measurement experiments, we evaluate the link-sharing and real-time performances of H-FSC, and determine the computation overhead     

一种新的曲线演化混合模型图像分割算法

本文在Mumford-Shah模型的基础上，将传统几何曲线演化的驱动力（图像梯度局部信息）、Mumford-Shah模型的全局信息以及水平集的符号距离函数统一在一个变分框架之下，完成曲线演化过程的数值计算。本混合模型无需重新计算演化曲线的初始位置，可选择较大时间步长。实验结果表明，新的混合模型既保留了原有曲线演化模型的优势，又能高效稳健、快速地完成曲线演化过程。     

弱小目标跟踪中利用样条曲线逼近的数据处理算法

弱小目标检测获得的量测数据由于各种不可预知因素的影响,包含了大量的误差和野值.同时由于系统和算法的敏感,微小的数据跳变就可以对目标信息的预测结果造成严重影响,引起跟踪偏差.针对这个问题,提出了一种利用样条逼近的分段多项式拟合思想和目标运动连续性的递推差分更新预测方法.首先根据样条函数和目标运动模型对已有数据进行平滑和预测,然后利用预测结果处理后续数据.这种方法能够实时地对目标信息数据的变化趋势进行更新,削弱误差和野值的影响,并根据此趋势预测后续数据.实验结果表明:此方法对存在突变的目标坐标数据具有很好的修正预测效果.     

A real-time curve tracer for the AC plasma display panel

A minicomputer-controlled system is used to automatically measure the wall charge transfer curve of a single cell in an ac plasma display panel. Curves can be plotted on a graphics display as fast as 5/s which allows real-time interaction with the user. The measurement technique is based on the ability to directly measure the wall charge from a single cell. The minicomputer controls the sustain voltage across the cell and obtains the resulting wall charge. It then does the tedious algebra needed to complete the transfer curve. The measured curves show numerous interesting effects. The influence of the state of the neighboring cells can clearly be seen. The duty factor of the sustain waveform has a strong influence on the transfer curve. An effect dependent on sustain frequency is presented that shows a transfer curve region with negative slope. The most interesting effect measured is a hysteresis in the transfer curve, in that a different curve is traced out as the cell goes from off to on than when it goes from on to off.     

A REAL—TIME C—V CLUSTERING ALGORITHM FOR WEB—MINING

In this letter, a real-time C-V (Characteristic-Vector) clustering algorithm is put forth to treat with vast action data which are dynamically collected from web site.The algo-fithm cites the concept of C-V to denote characteristic, synchronously it adopts two-value[0,1] input and self-definition vigilance parameter to design clustering-architecture.Vector Degree of Matching(VDM) plays a key role in the clustering algorithm, which determines the magnitude of typical characteristic.Making use of stability analysis, the classifications are confirmed to have reliably hierarchical structure when vigilance parameter shifts from 0.1 to 0.99.This non-linear relation between vigilance parameter and classification upper limit helps mining out representa-tive classifications from net-users according to the actural web resource, then administering system can map them to web resource space to implement the intelligent configuration effectually and reapidly.     

A real-time algorithm for the quantification of blood pressure waveforms

A real-time algorithm for quantification of biological oscillatory signals, such as arterial blood pressure (BP) is proposed which does not require user intervention and works on waveforms complicated by rapid changes in the mean level, frequency, or by the presence of arrhythmia. The algorithm is based on the continous independent assessment of the refractory period (RP). In the first stage, a sample of the signal is band-pass filtered. During the next stage: 1) the local maxima in the filtered signal are identified and their pulse amplitudes (PA) measured on the side opposite to the possible notch position and 2) those maxima whose PA exceeds some threshold are selected and an array of RP values is formed as a fraction of the moving estimate of the interval between successive selected peaks. Finally, the original signal is analyzed by means of two moving averages (MAs) with short and long averaging time intervals. The true peaks are determined as the maxima between intersections of MAs if the peak-to-peak or the intersection-to-intersection intervals since the previous peak and the previous intersection exceed the RP. The algorithm proved to be superior against three commercially available heartbeat detectors yielding an error rate of 0.09%.     

A real-time focusing algorithm for iris recognition camera

For fast iris recognition, it is very important to capture the user's focused eye image at fast speed. Previous researchers have used the focusing method which has been applied to general landscape scenes without considering the characteristics of the iris image. So, they take much focusing time, especially in the case of the user with glasses. To overcome such problems, we propose a new iris image acquisition method to capture focused eye images at very fast speed based on corneal specular reflection. Experimental results show that the focusing time for both users with and without glasses averages 480 ms, and we conclude that our method can be used for the real-time iris recognition camera.     

A fast piecewise linear approximation algorithm

A piecewise linear approximation algorithm is suggested in this paper. The algorithm is fast since it works in one pass through the given data and it does not require much memory space. Moreover the peak points are preserved and become corners of the resulting piecewise linear curve. Hence the algorithm is suitable for real time applications in which the peak points are carrying important information and therefore should be calculated accurately.     

椭圆曲线密码体制中点的数乘的一种快速算法

该文基于椭圆曲线密码体制,提出了椭圆曲线上点的数乘的一种快速算法.该算法通过引入2~k进制序列,缩短了乘数的相应序列长度,从而大大减少了点的数乘中的加法运算次数,并且分析了k的最佳选取,使得我们提出的算法比通常点的数乘算法效率提高了60％以上。     

A nonparametric statistical method for image segmentation using information theory and curve evolution.

In this paper, we present a new information-theoretic approach to image segmentation. We cast the segmentation problem as the maximization of the mutual information between the region labels and the image pixel intensities, subject to a constraint on the total length of the region boundaries. We assume that the probability densities associated with the image pixel intensities within each region are completely unknown a priori, and we formulate the problem based on nonparametric density estimates. Due to the nonparametric structure, our method does not require the image regions to have a particular type of probability distribution and does not require the extraction and use of a particular statistic. We solve the information-theoretic optimization problem by deriving the associated gradient flows and applying curve evolution techniques. We use level-set methods to implement the resulting evolution. The experimental results based on both synthetic and real images demonstrate that the proposed technique can solve a variety of challenging image segmentation problems. Futhermore, our method, which does not require any training, performs as good as methods based on training.     

A variable block size motion estimation algorithm for real-time H.264 video encoding

This paper presents an efficient variable block size motion estimation algorithm for use in real-time H.264 video encoder implementation. In this recursive motion estimation algorithm, results of variable block size modes and motion vectors previously obtained for neighboring macroblocks are used in determining the best mode and motion vectors for encoding the current macroblock. Considering only a limited number of well chosen candidates helps reduce the computational complexity drastically. An additional fine search stage to refine the initially selected motion vector enhances the motion estimator accuracy and SNR performance to a value close to that of full search algorithm. The proposed methods result in over 80% reduction in the encoding time over full search reference implementation and around 55% improvement in the encoding time over the fast motion estimation algorithm (FME) of the reference implementation. The average SNR and compression performance do not show significant difference from the reference implementation. Results based on a number of video sequences are presented to demonstrate the advantage of using the proposed motion estimation technique.     

A real-time exposure dose control algorithm for DUV excimer lasers

scan exposure model and analyzing the pulse-to-pulse energy fluctuation characteristics of DUV excimer lasers, a real-time dose regulation is implemented based on closed-loop feedback control, which especially focuses on reducing the effect of pulse energy overshot and pulse-to-pulse stochastic fluctuation. The experiment conducted on an ArF excimer laser with wavelength of 193 nm, repetition rate of 4 kHz, and pulse energy of 5 mJ confirms that such a real-time dose control algorithm is able to achieve a dose accuracy of above 0.89% even with only 20 pulses. It is fully expected that this algorithm will not only meet increasingly stringent dose accuracy requirements for sub-half-micron lithography, but also be helpful to improve lithography throughput as well as efficiency.     

A simple adaptive algorithm for real-time processing in antenna arrays

A new adaptation algorithm designed for real-time data processing in large antenna arrays is presented. The algorithm is used to determine the set of filter coefficients (weights) which minimizes the mean-square error in a multidimensional linear filter. The algorithm forms an estimate of the target signal, which is assumed to be of interest, in the presence of interfering noises. It is assumed that the direction of arrival and spectral density of the target signal are known a priori. No such information is assumed to be available regarding the structure of the interfering noise field. The a priori target information is incorporated directly into the adaptation procedure using a modified gradient descent technique. The mathematical convergence properties of the algorithm are presented and a computer simulation experiment is used as an illustration. It is shown that as the number of iterations becomes large, the expected value of the adaptive solution converges to the minimum mean-square-error solution. It is further shown that the variance of the adapted filter about the optimum solution can be made arbitrarily small by appropriate choice of a scalar constant in the algorithm. These results are based on the assumption that the array signals are Gaussian and that successive time samples are statistically uncorrelated. Thus, the new algorithm is shown to converge to the optimum processor in the limit as the number of adaptations becomes large. Any disadvantage which may arise in the use of such an asymptotically optimum system is offset by the extreme simplicity of the adaptive procedure. This simplicity should prove to be particularly useful in many of the practical array processing problems recently encountered in seismic and sonar data processing.     

一种改进实时图像去雾的暗原色先验算法

针对暗原色先验图像去雾算法运行时间长,天空区域分割耗时,复原图像中存在方块效应以及整体偏暗等缺点,提出一种改进的实时图像去雾暗原色先验算法。在暗通道求取时,使用快速最小值滤波,加快传统暗通道求取最小值排序的时间;在大气光求取时,使用像素值限定的方法快速排除天空区域,使用暗通道图像剩余最亮部分对应原图像像素值的均值,有效避免原算法中求取大气光值过大导致复原图像失真的现象;在透射率的优化时,使用Sobel边缘检测与求取图像二阶导数图像,得到精细的透射率,改善了细化透射率的时间复杂度;对最终图像采取伽码变换,提高图像亮度。实验结果表明,与原暗通道先验算法相比,此算法有效提高了算法的实时性。     

实时网络的分布式调度

针对主—从结构实时网络的性能特点,提出了一种基于EDF的主节点分布式实时任务调度算法,给出了该调度算法下实时任务组的可调度的充分条件。仿真测试表明,该调度算法满足实时约束,适合于主—从结构的实时网络调度。     

A curve evolution approach to object-based tomographic reconstruction

We develop a new approach to tomographic reconstruction problems based on geometric curve evolution techniques. We use a small set of texture coefficients to represent the object and background inhomogeneities and a contour to represent the boundary of multiple connected or unconnected objects. Instead of reconstructing pixel values on a fixed rectangular grid, we then find a reconstruction by jointly estimating these unknown contours and texture coefficients of the object and background. By designing a new "tomographic flow", the resulting problem is recast into a curve evolution problem and an efficient algorithm based on level set techniques is developed. The performance of the curve evolution method is demonstrated using examples with noisy limited-view Radon transformed data and noisy ground-penetrating radar data. The reconstruction results and computational cost are compared with those of conventional, pixel-based regularization methods. The results indicate that the curve evolution methods achieve improved shape reconstruction and have potential computation and memory advantages over conventional regularized inversion methods.     

Simplified algorithm for Laguerre approximation of URC networks

A simplified algorithm for the efficient computation of sequences required in the Laguerre transform signal analysis of transients on uniformly distributed RGC lines is derived     

A modified-set partitioning in hierarchical trees algorithm for real-time image compression

Among all algorithms based on wavelet transform and zerotree quantization, Said and Pearlman’s set partitioning in hierarchical trees (SPIHT) algorithm is well known for its simplicity and efficiency. SPIHT’s high memory requirement is a major drawback to hardware implementation. In this study, we present a modification of SPIHT named modified SPIHT (MSPIHT), which requires less execution time at a low bit rate and less working memory than SPIHT. The MSPIHT coding algorithm is modified with the use of one list to store the coordinates of wavelet coefficients instead of three lists of SPIHT; defines two terms, number of error bits and absolute zerotree; and merges the sorting pass and the refinement pass together as one scan pass. Comparison of MSPIHT with SPIHT on different test image shows that MSPIHT reduces execution time at most 7 times for coding a 512 × 512 grayscale image; reduces execution time at most 11 times at a low bit rate; saves at least 0.5625 MB of memory; and reduces minor peak signal-to noise ratio (PSNR) values, thereby making it highly promising for real-time and memory limited mobile communications. Published in Russian in Radiotekhnika i Elektronika, 2008, Vol. 53, No. 6 pp. 676–685. The text was submitted by the authors in English.