关于正整数n的平方部分数列的均值公式

利用解析的方法来研究平方序列的均值，从而得出几个有趣的渐进公式．     

多维视觉信息DWT-混沌加密技术研究

针对多维视觉信息图像和视频等的加密问题进行研究,提出一种基于离散小波和混沌序列的加密技术。该方法利用多维可视信号宿主的巨大可转换状态空间及各中间状态间的转换关系,获得一种视觉信息最佳保护系统结构框架模型,根据该模型,用DWT变换压缩知化视觉特征,用混沌序列破坏知化视觉特征,达到保护多维可视信息安全的目的。给出一个具体应用实例,通过仿真实验证明了该算法的有效性。     

The k-Error Linear Complexity and the Linear Complexity for pq^n-Periodic Binary Sequences

The k-error linear complexity and the linear complexity of the keystream of a stream cipher are two important standards to scale the randomness of the key stream. For a pq^n-periodic binary sequences where p, q are two odd primes satisfying that 2 is a primitive root module p and q^2 and gcd（p-1, q-1） = 2, we analyze the relationship between the linear complexity and the minimum value k for which the k-error linear complexity is strictly less than the linear complexity.     

利用复杂网络来研究tRNA序列的进化

根据点突变和互补复制的进化机制构建tRNA序列相似度平行网络和反平行网络并研究了网络的特征．分析发现当相似度很大时，tRNA基因网络出现了无标度（scale—free）的特征．其次，还比较了平行网络和反平行网络的特征，发现在相同的条件下，反平行网络中的tRNA序列间的关系比平行网络中更密切，它们之间的相似程度更高．这同时说明现代tRNA序列由互补复制机制进化的可能性更大．最后根据点突变和互补复制的进化机制建立了一个粗糙的tRNA进化模型．结果发现模型tRNA相似度网络在0．3≤ε≤0．5条件下，不仅和真实tRNA相似度网络有局部的相似行为，而且网络的整体行为也是相似的．因此现代tRNA序列的合理的进化机制应该是上述两种机制的混合．     

跳频通信系统中的迟入网技术研究

介绍了超短波跳频电台系统结构及基本原理,分析了时间信息(TOD)与3种跳频同步分类,提出了一种迟入网同步方案。     

传统扩频与混沌扩频的CDMA系统在Rappaport Indoor信道下的性能比较

 对Logistic映射的混沌序列作为扩频序列构成的混沌扩频CDMA系统与传统的m序列扩频CDMA系统进行了对比研究,并且对其二者在Rappaport Indoor信道下的性能在SPW上进行了仿真、分析,具有重要实际意义.     

采用混沌扩频序列的异步码分多址通信系统仿真

为了获取适用于异步码分多址系统的混沌序列 ,提出了一种基于扩频序列性能分析准则的优选方法 ,并用系统仿真的方法进行了验证。通过对异步码分多址系统的性能分析 ,总结了扩频序列的性能准则 ,以此为依据对初值不同的混沌序列进行筛选 ,可以得到性能优异的混沌扩频序列。采用 Monte Carlo的方法 ,在无线衰落信道下对采用混沌序列和 Gold序列的异步码分多址系统进行了仿真。结果表明 :优选的混沌序列性能要优于 Gold序列 ,是扩频序列的一种新的选择     

采用时空混沌耦合映象格子产生混沌扩频序列

利用耦合映象格子这一具体的时空混沌模型来产生混沌扩频序列，研究了产生混沌扩频序列的方法，并对序列特性进行了分析，结果证明产生出来的序列扩频特性性能良好，可以应用于扩频通信系统。     

A genetic algorithm on multiple sequences alignment problems in biology

The study and comparison of sequences of characters from a finite alphabet is relevant to various areas of science, notably molecular biology. The measurement of sequence similarity involves the consideration of the possible sequence alignments in order to find an optimal one for which the “distance” between sequences is minimum. In biology informatics area, it is a more important and difficult problem due to the long length (100 at least) of sequence, this cause the compute complexity and large memory require. By associating a path in a lattice to each alignment, a geometric insight can be brought into the problem of finding an optimal alignment, this give an obvious encoding of each path. This problem can be solved by applying genetic algorithm, which is more efficient than dynamic programming and hidden Markov model using commomly now. Foundation item: Supported by Zi-qiang Foundation of Wuhan University and Open Foundation of the State Key-Laboratory of Software Engineering, Wuhan University Biography: Shi Feng(1966-), male, Associate professor, research direction: bioinformatics.     

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.