基于人工神经网络的人员安全疏散反应时间研究

主要研究了基于Levenberg-Marquardt算法的人工神经网络的火灾时人员疏散反应时间的可靠性和可行性。首先介绍了人员疏散现状调研和LP神经网络背景特点,然后将问卷调查、疏散演练基于同一平台,建构人员疏散反应数学模型,最后通过LP神经网络进行实际测试和分析,验证了人员疏散反应时间数学模型的可靠性。     

神经网络集成方法在火灾分析中的应用

采用神经网络集成方法对我国31个地区的经济总量、消防基本投入、火灾损失之间的关系进行定量分析,研究发现神经网络集成方法能有效地反应各地区经济发展水平、消防基本投入与火灾损失之间的内在联系。     

A novel facial emotion recognition scheme based on graph mining

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. To reduce the number of generated sub-graphs, overlap ratio metric is utilized for this purpose. After encoding the final selected sub-graphs, binary classification is then applied to classify the emotion of the queried input facial image using six levels of classification. Binary cat swarm intelligence is applied within each level of classification to select proper sub-graphs that give the highest accuracy in that level. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the final system accuracy was 90.00%. The results show significant accuracy improvements (about 2%) by the proposed system in comparison to current published works in SAVEE database.     

Gabor-CNN for object detection based on small samples

Object detection models based on convolutional neural networks (CNN) have achieved state-of-the-art performance by heavily rely on large-scale training samples. They are insufficient when used in specific applications, such as the detection of military objects, as in these instances, a large number of samples is hard to obtain. In order to solve this problem, this paper proposes the use of Gabor-CNN for object detection based on a small number of samples. First of all, a feature extraction convolution kernel library composed of multi-shape Gabor and color Gabor is constructed, and the optimal Gabor convolution kernel group is obtained by means of training and screening, which is convolved with the input image to obtain feature information of objects with strong auxiliary function. Then, the k-means clustering algorithm is adopted to construct several different sizes of anchor boxes, which improves the quality of the regional proposals. We call this regional proposal process the Gabor-assisted Region Proposal Network (Gabor-assisted RPN). Finally, the Deeply-Utilized Feature Pyramid Network (DU-FPN) method is proposed to strengthen the feature expression of objects in the image. A bottom-up and a top-down feature pyramid is constructed in ResNet-50 and feature information of objects is deeply utilized through the transverse connection and integration of features at various scales. Experimental results show that the method proposed in this paper achieves better results than the state-of-art contrast models on data sets with small samples in terms of accuracy and recall rate, and thus has a strong application prospect.     

基于一类弱连续T-模的模糊Hopfield神经网络研究

基于一般的弱连续T-模与取大（V）模糊算子的复合,建立了具有一般意义的动态模糊神经网络——模糊Hopfield神经网络,并系统分析了该动态系统的性能：在Hamming距离意义下证明了该网络是稳定的,而且其平衡点（吸引子）具有全局Lyapunov稳定性。最后,提供了一种有效的学习算法。     

自行火炮群的野战移动自组织网络

提高野战条件下的通信保障能力是当前我军炮兵部队信息化建设的一项重要内容,需要在原有通信方式的基础上探索新的途径。结合自行火炮群的作战指挥特点和无线自组织网的优点,研究了适用于自行火炮群的野战移动自组织网络,从结构体系、指挥网络的管理以及路由协议的选择等方面探讨了自组织网相关技术在自行火炮群作战中的具体应用。     

认知无线电专题讲座(四) 第8讲 下一代网络:认知网络

认知网络是一种具有认知能力和认知过程的网络,它能够感知网络当前的状况,并根据当前的状况来计划、决定并行动。文中首先介绍了认知网络的基本概念及设计目标,然后描述了认知网络的特征和一种架构——CogNet。最后提出了认知网络的潜在应用及在今后的研究中需解决的几个主要问题。     

GPRS核心网自动拨测系统的设计与实现

GPRS核心网自动拨测系统是在GPRS核心网接口接入,以信令仿真方式向各实体发起拨测业务,从而实现业务可用情况、网元承载信令、路由通畅性、业务感知等指标的周期性自动测试的新一代业务测试系统。该系统具有独创性和前瞻性的特点,填补了国内外相关领域的空白。     

嵌入式工业级无线网关的设计与实现

文中提出了基于嵌入式Linux的异构网络互通互连方案,设计实现了一种基于ARM9平台的嵌入式Linux的无线网关。通过测试验证了以太网LAN和802.11无线网络之间互通和无线网关的可行性。     

基于神经网络的混合双滤波器自适应目标跟踪算法

在分析近期基于神经网络数据融合的目标跟踪算法的基础上,结合一种新的自适应滤波模型(NAF)和速度估计自适应跟踪算法(AVE),提出了基于神经网络混合双滤波器的机动目标自适应跟踪算法(NHDF).该算法通过在线自动调节网络输出进行过程噪声方差融合,降低了现有算法因系统方差的调整不当而带来的精度损失.理论分析及仿真结果证明,与"当前"统计模型、速度自适应模型和新的自适应模型算法相比,该算法具有跟踪精度高,自适应能力强的优点.