傅里叶级数的曲线仿真应用及算法

以电力系统日负荷曲线为例，应用傅里叶级数进行仿真，并提出用线性化回归方法求取傅里叶级数系数的新算法。     

Spectral analysis of phylogenetic data

The spectral analysis of sequence and distance data is a new approach to phylogenetic analysis. For two-state character sequences, the character values at a given site split the set of taxa into two subsets, a bipartition of the taxa set. The vector which counts the relative numbers of each of these bipartitions over all sites is called a sequence spectrum. Applying a transformation called a Hadamard conjugation, the sequence spectrum is transformed to the conjugate spectrum. This conjugation corrects for unobserved changes in the data, independently from the choice of phylogenetic tree. For any given phylogenetic tree with edge weights (probabilities of state change), we define a corresponding tree spectrum. The selection of a weighted phylogenetic tree from the given sequence data is made by matching the conjugate spectrum with a tree spectrum. We develop an optimality selection procedure using a least squares best fit, to find the phylogenetic tree whose tree spectrum most closely matches the conjugate spectrum. An inferred sequence spectrum can be derived from the selected tree spectrum using the inverse Hadamard conjugation to allow a comparison with the original sequence spectrum. A possible adaptation for the analysis of four-state character sequences with unequal frequencies is considered. A corresponding spectral analysis for distance data is also introduced. These analyses are illustrated with biological examples for both distance and sequence data. Spectral analysis using the Fast Hadamard transform allows optimal trees to be found for at least 20 taxa and perhaps for up to 30 taxa. The development presented here is self contained, although some mathematical proofs available elsewhere have been omitted. The analysis of sequence data is based on methods reported earlier, but the terminology and the application to distance data are new.     

《刑法》第267条第二款之我见

抢劫犯罪是严重侵犯公民人身权、财产权的犯罪,历来为各国法律所重点打击。但我国刑法第267条第二款的规定“携带凶器抢夺的,依照本法第263条的规定定罪处罚”暴露出明显的不合理因素。鉴于此,本文从抢劫罪的定性,罪质,与抢夺罪的本质区别,刑法预防目的等万面进行探研,得出对这一条款进行适当修改的结论。     

一种基于傅里叶变换的运动图像全盲认证方法

利用运动图像傅里叶变换幅度谱的带状调制特性,提出一种针对运动图像的全盲认证方法,实现了对运动图像经过修改、移动、区域填充以及非运动图像上填充运动图像块两种情况下的篡改区域检测与定位.实验验证了其有效性及对噪声的鲁棒性.     

一种基于FFT的高动态GPS信号快速捕获方法

对高动态GPS信号快速捕获问题进行了研究,提出了一种适应高动态环境,捕获时间短的捕获方法。该方法采用多普勒频域串行捕获,时域由FFT代替滑动相关的并行捕获的二维策略,从而大大提高了高动态GPS接收机的信号捕获性能。分析了基于FFT的快速捕获原理和软件实现,并通过对实测的GPS信号的捕获验证了该捕获方法的正确性。     

基于高分辨雷达的运动目标参数估计方法研究

根据运动目标的频域回波的特点，深入研究了一种具有多项式相位结构的运动目标回波仿真模型，并提出了基于该模型的多特征参数提取方法。该方法基于匹配傅立叶变换理论，依据频域雷达目标回波特征构造匹配函数，对目标回波数据进行匹配傅立叶变换，变换结果的主瓣坐标反映了目标散射点的距离及速度信息。大量的仿真实验结果证明，该方法十分有利于进行运动目标的特征提取。根据对仿真结果的分析，进一步给出了改进算法，使得在较低信噪比情况下也能够有效的检测出目标上的散射点的距离与速度参数。     

基于RSPWVD-Hough的多分量LFM信号检测

由于多分量LFM信号的双线性时频分布（BTFD）存在交叉项的干扰，所以在低信噪比条件下直接在时频平面难于进行检测，采用重排平滑伪魏格纳维尔分布（RSPWVD），能在抑制交叉项的同时提高时频聚集性，并利用Hough变换检测图像中直线的原理，将多分量LFM信号的检测问题转换为在参数空间寻找局部极大值的问题，由于Hough变换运算量较大，提出一种在平滑重排后进行设定门限处理的方法，仿真实验表明，该方法可以在抑制噪声和交叉项的同时大大减少运算量。     

基于秘密共享方案的小波混沌数字水印算法

在对小波域混沌数字水印算法研究的基础上,引入Shamir理论秘密共享思想,提出一种新的基于Shamir秘密共享的小波混沌数字水印算法。新算法将小波分解所得到的子图作为分存信息的保存对象,嵌入部分或者全部的数字水印信息。在水印的提取中,根据Shamir理论利用部分子信息就可以恢复出初始水印信息。实验表明该算法拥有好的视觉效果,提高了传统算法的鲁棒性,是一种实际可行的数字水印算法。     

整流电路的功率问题研究

利用谐波分析等方法分别探讨单相全波整流电路的功率问题．分析结果表明：不考虑传输损耗的理想情况下，在全波整流电路中，输出功率与输入功率之比为1：1．实现了谐波分析法在整流电路功率问题研究中的应用，有助于对整流电路的功率问题以及谐波分析法有进一步的理解和认识．     

Blurred Defocused Image Restoration Based on FRFT

A technique for restoring the blurred image resulted from defocusing of the lens is proposed in this paper, which is based on fractional Fourier transform （FRFT）.The FRFT, as a powerful tool for the analysis of time-varying signals, is closely connected with the optical imaging system. FRFT also can describe optical imaging process just like Fresnel diffractions, so a defocused imaging model based on FRFT is established to explain the blur phenomena of defocusing image. The defocused imaging model is greatly different from the traditional point spread function （PSF） model, and enables to uncover the blur nature of non-focus image. Then, an image restoration method using the novel model is proposed to handle the blurred defocused image. The method adopted a new iterative phase retrieval approach which can approximately estimate phase signals from intensity signals of a single defocused image by means of FRFT. Restoring image may acquire sharp image by implementing inverse FRFT on complex image signal made from the estimated phase signals and intensity signals. Experimental results demonstrate that the method is effective in restoring blurred defocused image.