一种超混沌自动转换系统的设计与分析

在一种超混沌系统的基础上,通过改变系统第三个方程中的非线性项的方法,构造了一个新的超混沌系统,并利用常用开关函数来实现超混沌自动转换系统。通过matlab对超混沌系统进行仿真,产生超混沌吸引子,并对其子系统和转换系统Lyapunov指数进行分析与研究,仿真满足超混沌系统产生必要条件。结果表明所设计的自动转换系统可以实现两个超混沌系统的相互转换。     

基于Walsh函数系的椭圆球面波脉冲波形重构方法

目前PSWF的脉冲产生方法在硬件实现方面有着编程复杂,计算量大,资源消耗多等制约因素,因此亟需一种适合实时产生PSWF脉冲信号的方法。通过分析Walsh函数系的特点和产生原理,提出了一种基于Walsh函数系的PSWF脉冲波形重构方法。其中,Walsh系数可以通过已有的PSWF数值点与P编号的Walsh矩阵求解得出,再截取所需精度的Walsh系数参与重构PSWF脉冲波形,从而达到降低存储量的目的。由于Walsh码型中的±1与数字电路中的01有着天然对应的关系,重构时只需将Walsh系数相加减,从而降低计算量。仿真结果表明,利用Walsh函数系可以较好地重构PSWF脉冲波形,且算法简单,避免了乘法运算,降低了计算量和存储量,有利于工程实现。     

Learning shape and texture progression for young child face aging

Face aging (FA) for young faces refers to rendering the aging faces at target age for an individual, generally under 20s, which is an important topic of facial age analysis. Unlike traditional FA for adults, it is challenging to age children with one deep learning-based FA network, since there are deformations of facial shapes and variations of textural details. To alleviate the deficiency, a unified FA framework for young faces is proposed, which consists of two decoupled networks to apply aging image translation. It explicitly models transformations of geometry and appearance using two components: GD-GAN, which simulates the Geometric Deformation using Generative Adversarial Network; TV-GAN, which simulates the Textural Variations guided by the age-related saliency map. Extensive experiments demonstrate that our method has advantages over the state-of-the-art methods in terms of synthesizing visually plausible images for young faces, as well as preserving the personalized features.     

Current–voltage curve translation by bilinear interpolation

By means of bilinear interpolation and four reference current–voltage (I–V) curves, an I–V curve of a photovoltaic (PV) module is translated to desired conditions of irradiance and PV module temperature. The four reference I–V curves are measured at two irradiance and two PV module temperature levels and contain all the essential PV module characteristic information for performing the bilinear interpolation. The interpolation is performed first with respect to open‐circuit voltage to account for PV module temperature, and second with respect to short‐circuit current to account for irradiance. The translation results over a wide range of irradiances and PV module temperatures agree closely with measured values for a group of PV modules representing seven different technologies. Root‐mean‐square errors were 1·5% or less for the I–V curve parameters of maximum power, voltage at maximum power, current at maximum power, short‐circuit current, and open‐circuit voltage. The translation is applicable for determining the performance of a PV module for a specified test condition, or for PV system performance modeling. Copyright © 2004 John Wiley & Sons, Ltd.     

一种快速自适应全局运动估计算法的研究

该文提出一种快速自适应全局运动估计算法。该方法从分析块匹配运动矢量统计特性出发,通过 引入一个可预设置参数,计算当前帧与参考帧之间的基本平移矢量,并自适应地采取混合全局运动、局部运 动估计的算法处理不同特征的源数据.仿真结果表明,与传统方法相比,该文算法复杂性低、处理延时小、 更利于硬件实现,在PSNR变化不大的情况下,编码效率有较大的改善.     

焙烧温度和盐酸浓度对硅藻土负载铁系后过渡金属催化剂的影响

采用红外光谱和扫描电子显微镜对不同焙烧温度和不同浓度盐酸处理的硅藻土进行了分析,考察了硅藻土的焙烧温度和盐酸处理浓度对负载铁系后过渡金属催化剂活性和对乙烯聚合性能的影响。结果表明:最佳焙烧温度为600℃,酸化时HCl的最佳浓度为5%;使乙烯在40℃及n(Al)/n(Fe)为1500的条件下进行淤浆聚合,催化剂活性为707kg/(mol·h),制得了熔融温度为123.9℃,结晶度为65.2%～67.8%的聚乙烯。     

Classification‐Based Approach for Hybridizing Statistical and Rule‐Based Machine Translation

In this paper, we propose a classification‐based approach for hybridizing statistical machine translation and rule‐based machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto‐evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut‐off method. In our experiments, using the aforementioned cut‐off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% — a 5.0% improvement over existing methods.     

Policy translation and configuration using dynamic template

To solve the problem of complex,cumbersome and error-prone configuration of security devices caused by the heterogeneous configuration modes in complex networks,a dynamic template-based scheme for translating and configuring policy was proposed.In detail,considering the code’s features,the code-based template for translating policies was constructed to configure the command line conversion,and the keyword comparison method was used to ensure the accuracy of policy configuration.Experiments show that the scalability and the accuracy of the proposed scheme.     

Graph-based Lexicalized Reordering Models for Statistical Machine Translation

Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.     

基于双树复小波变换的多聚焦图像融合方法

针对同一场景的多聚焦图像融合,提出了一种基于双树复小波变换(DT-CWT)的图像融合新算法.首先利用DT-CWT对图像进行多尺度和多方向分解,并根据双树复小波分解域各子带的系数特性定义了图像局部方向对比度,然后针对高频分量系数的选择,采用基于方向对比度的融合规则,而在低频域采用图像清晰度为测度的融合策略.实验结果表明,该算法能够很好地将多聚焦图像中的重要信息提取并注入到融合图像中,与其他方法相比较,取得了更好的融合效果,提高了融合图像的质量.