具有大量错误结点的超立方体网络中的高效路由算法的设计与讨论

该文提出了容错超立方体网络的一个很自然的机关报概念；局部连通性；讨论了两种类型的局部连通性；大局中部k-维子立方体连通性和局部子立方体连通性；一个局部连通的超立方体网络可容许大量错误结点且能确保超立方体网络是全局连通的；给出了满足局部连通性条件的超立方体网络中的几个高效的容错路由算法，文中的容错路由算法是分布式的和基于局部信息的，因而具有很强的实际意义。  

具有大量错误结点的超立方体网络中并行路由算法

本文讨论具有大量错误结点的超立方体网络中的并行路由算法。假定Hn是一个局部k-维子立方体连通用的n-维超立方体网络，本文提出的并行路由算法能够找出至少K=min（Dk(u),Dk(v）条并行路径，其中每一条路径的长度不超过（dH(Uk,Vk）＋3）2^k。该算法的时间复杂度为O（Kn2^k）。这里，Dk(u）和Dk(v）分别代表源结点u和目的结点v的正确的邻结点个数（不考虑u和v所在的k－维子立方体内部的邻结点），dH(Uk,Vk）代表源结点u和目的结点v所在的两个k－维子立方体Uk和Vk之间的海明距离。本文还考察了了k=3的特殊情况，在k=3并且有分别不超过12．5％和25％的错误结点的情况下，该算法的时间复杂度为O（Kn），并且每一条路径的路径长度分别在大约1．5和2倍源结点和目的结点之间的海明距离之内。该算法只要求结点知道其邻结点的状态，而无需知道整个网络信息，也就是说，该算法是基于局部信息的，因而该算法具有很强的实际意义。  

基于简化PCNN的车牌定位算法

为了提高车牌定位效率，提出一种混合简化脉冲耦合神经网络(PCNN)和快速连通域标记的车牌定位算法。基于简化PCNN进行图像增强，利用车牌字符的连通域特征、纹理特征和结构特征对增强后的二值图像进行过滤、筛选，得到图像中大致车牌区域，再对所得区域左边界起始的左扩展区域做垂直投影，确定车牌中汉字区域，从而定位车牌。实验结果表明，该算法性能优于其他车牌定位算法，其定位准确率为97.5%。  

Theory of granular lattices and its applications

Based on the concept of components of elements of a complete lattice this paper proposed the theory of granular lattices and proved that a topological space X is locally connected if and only if the lattice Ω(X) of its topology is a granular lattice. Moreover, this paper discussed compactness of abstract semantics on certain granular lattices and proved that the semantics is compact if it is continuous in a natural sense, and as a corollary, the compactness of Lukasiewicz's semantics was clarified.  

Face localization and tracking in the neural abstraction pyramid

One of the major tasks in some human–computer interface applications, such as face recognition and video telephony, is to localize a human face in an image. In this paper, we propose to use hierarchical neural networks with local recurrent connectivity to solve this task not only in unambiguous situations, but also in the presence of complex backgrounds, difficult lighting, and noise. The networks are trained using a database of gray-scale still images and manually determined eye coordinates. They are able to produce reliable and accurate eye coordinates for unknown images by iteratively refining initial solutions. Because the networks process entire images, there is no need for any time-consuming scanning across positions and scales. Furthermore, the fast network updates allow for real-time face tracking. In this case, the networks are trained using still images that move in random directions. The trained networks are able to accurately track the eye positions in the test image sequences.  

具有大量错误结点的超立方体网络中的单播路由算法的设计与分析

本文讨论具有大量错误结点的超立方体网络中的单播路由算法，假定Hn是一个局部3－维子立方体连通的n-维超立方体网络并且每一个基本的3－维子立方体中分别最多有1个和2个错误结点，本文提出的单播路由算法能够在线性时间找到路径长度分别为源结点和目的结点之间大约1．5倍和2倍海明距离的次优路径，我们提出的单播路由算法只需要结点知道其邻结点的状态，而无需知道整个网络信息，也就是说，该算法是基于局部信息的，因而该算法具有很强的实际意义。  

Synchronization of Locally Coupled Neural Oscillators

A new method of controlling Fitzhugh-Nagumo (F-N) neural oscillators, Fitzhugh [1], with local coupling is presented. It is proved that through the use of an additive closed-loop controlling action that entrains each neural oscillator to a goal behavior, necessary and sufficient conditions for the occurrence of synchronization in networks of unidirectionally self-connected neural oscillators are obtained in terms of asymptotic stability. These conditions suggest that rapid global synchronization can be achieved using sufficiently strong local inhibitory connections.  

一种层次化的Data Matrix实时解码方法

在实际应用中，Data Matrix二维条形码的解码效果会受到不均匀光照和复杂背景的影响。为此，提出一种层次化的Data Matrix实时解码方法。利用大津法将条码图像的前景和背景进行分割，得到二值化的条码图像，对其进行区域定位和精确定位。在此基础上，设计基于数字信号处理的二维条形码快速解码终端。实验结果表明，该解码方法具有较好的实时性和较高的鲁棒性。  

异构传感器网络中对密钥建立方案

针对现有异构传感器网络(HSN)密钥预分配方案的安全问题，提出一种基于部署知识和密钥链技术的对密钥建立方案。将部署区域划分成多个单元，整个HSN网络划分成簇。在部署区域中，相邻节点使用预分配密钥信息建立共享密钥。在节点部署完成后，当两相邻节点不能建立共享密钥时，通过其他高能节点为其分配共享密钥。理论分析和模拟结果表明，该方案的存储开销和计算开销小，局部连通率高，对抗节点俘获的弹性性能和安全性能好。  

Locally connected spanning trees in cographs, complements of bipartite graphs and doubly chordal graphs

A spanning tree T of a graph G=(V,E) is called a locally connected spanning tree if the set of all neighbors of v in T induces a connected subgraph of G for all v∈V. The problem of recognizing whether a graph admits a locally connected spanning tree is known to be NP-complete even when the input graphs are restricted to chordal graphs. In this paper, we propose linear time algorithms for finding locally connected spanning trees in cographs, complements of bipartite graphs and doubly chordal graphs, respectively.