层析成像的模糊-神经网络重建方法

考虑投影数据不足时，射线层析成像的离散重建算法难以取得较好效果的情况，利用模糊理论建立了表示物体衰减系数的连续函数，用神经网络学习算法确定该连续函数中的待定参数．提出了一种适于投影数据或投影方向不够时的CT图像重建算法．计算机仿真结果显示了该方法在投影数据严重缺少时的良好效果。     

Efficient and power-awareness query over sensor networks

Sensor networks consisted of low-cost, low-power, multifunctional miniature sensor devices have played an important role in our daily life. Light and humidity monitoring, seismic and animal activity detection, environment and habitat monitoring are the most common applications. However, due to the limited power supply, ordinary query methods and algorithms can not be applied on sensor networks. Queries over sensor networks should be power-aware to guarantee the maximum power savings. The minimal power consumption by avoiding the expensive communication of the redundant sensor nodes is concentrated on. A lot of work have been done to reduce the participated nodes, but none of them have considered the overlapping minimum bounded rectangle (MBR) of sensors which make them impossible to reach the optimization solution. The proposed OMSI-tree and OMR algorithm can efficiently solve this problem by executing a given query only on the sensors involved. Experiments show that there is an obvious improvement compared with TinyDB and other spatial index, adopting the proposed schema and algorithm.     

中枢型尼古丁受体与阿尔茨海默病

阿尔茨海默病是一种以渐进性的认知功能障碍为主要特征的神经退行性疾病，该病最终会导致死亡，是痴呆病中最常见的一种类型。近年来研究发现中枢尼古丁受体在AD的发病中起着非常重要的作用，本文对此进行综述。     

Conflict Pattern Analysis: Preparing the Ground for Participation in Policy Implementation

The participation of non-state actors in implementation processes is often understood as a means to increase compliance efficiency. But the implementation of spatial policies frequently focuses on pre-established goals, processes and instruments and thus renders difficult open discourse and shared decision-making. This paper introduces conflict pattern analysis (CPA) as a tool that supports the analysis of the actual actor constellation in order to define efficient approaches that avoid common problems of participatory processes. CPA is a semi-formalised method that helps to identify key-actors, their relations and interaction amongst each other as well as their core beliefs, interests and resources. It aggregates this information to interaction patterns that can be compared, classified and linked to different participatory methods on a theoretically informed basis. Particularly on the local and regional level, this could be the first step for successful (participatory) implementation strategies.     

Samples Selection for Artificial Neural Network Training in Preliminary Structural Design

An artificial neural network (ANN) is applied in the preliminary structural design of reticulated shells. Major efforts are made to enhance the generalization ability of networks through well-selected training samples. Number-theoretic methods (NTMs) are adopted to generate samples with low discrepancy, i.e.uniformly scattered in the domain, where discrepancy is a quantitative measurement of the uniformity. The discrepancy of the NTM-based sample set is 1/6-1/7 that of samples with equal spacing. In a case study,networks trained by NTM-based samples are compared with those trained by equal-spaced samples in generalizing performance. The results show that both the computational precision and stability of the former ANNs are more satisfactory than those of the latter. It is concluded that the flexibility of ANNs in generalizing can be effectively increased by use of uniformly distributed training samples rather than simply piling data.More reliable uniformity should be obtained, however, through NTMs instead of equal-spaced samples.     

人工神经网络紫外分光光度法同时测定苯和甲苯

应用三层ANN_BP网络解析苯和甲苯的吸收光谱 ,不经分离 ,用紫外分光光度法同时测定苯和甲苯 .使用改进的BP算法 ,避免了神经网络学习过程中可能产生的麻痹现象 ,提出了目标向量的简单变换方法及便于网络参数选择的收敛评价函数 .实验验证了方法的有效性 ,同时表明 ,苯在 0 - 72 0mg/L和甲苯在 0 - 84 0mg/L范围内服从比尔定律     

神经网络自适应控制器设计

对前馈神经网络用于动态系统的辨识、自适应控制进行了分析和数学推导，给出了自适应神经网络控制器的设计方法．最后通过仿真实例进行了说明．     

无线异类数据网服务质量体系结构解决方案

设计了一套具有高性能的适合于移动数据网（超2．5G）和无线本地区域网（WLAN）组成的综合数据网的网络体系结构，提供基于预留端到端的QoS模型，使用带宽适应算法支持端到端的QOS，提高了系统资源的利用率，减少了呼叫拥塞概率和交接丢包概率，解决了2个系统QoS类不匹配等问题，平衡了2个系统的传输能力。     

Artificial Neural Network for Combining Forecasts

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统计模式识别的研究

模式识别的基本目标就是在有监督和无监督的情况下进行分类,在模式识别的各种模型中,基于统计的方法已经被广泛的研究并应用于实际.一些新的技术和方法的引入（神经网络和支持向量机方法）也促进了该领域发展,文章研究了基于统计的模式识别的进展情况,给出了模式识别的概念、原理、方法并对各种方法进行了相关的评述.