Low temperature synthesis of aluminium titanate by an aqueous sol-gel route

Formation of aluminium titanate (AT) has been achieved at low temperature through sol-gel process using boehmite and titanium hydroxide as precursors by controlling the particle size at nanoscale followed by in-situ peptisation. The formations of AT phase, particle size distributions, sintering and thermal expansion characteristics, and microstructural features have been reported. DTA and XRD analysis have been performed to confirm the formation of AT. A 94% relative density was obtained for aluminium titanate sintered at 1550 °C with controlled grain size in the range of 2-3 μm.     

基于ANN的声目标识别系统及其DSP实时实现

介绍了一种基于人工神经网络(ANN)的声目标识别系统,概述了用MATLAB专用工具箱对神经网络权值进行训练及仿真的过程,叙述了ANN目标识别系统的数字信号处理器(DSP)实时实现过程,并着重分析定点实现过程中程序变量的定标、非线性运算的实现、溢出的处理等关键步骤.对不同字长的识别结果进行比较表明,基于定点实时实现的系统数据保持很高的精度,可以得到与浮点处理相同的识别率.     

基于DTW算法的语音识别系统实现

动态时间归整(DTW)算法的实现简单有效,在孤立词语音识别系统中得到了广泛的应用.介绍了将DTW算法移植到TMS320VC5402上实现孤立词语音识别的原理、系统硬件组成和软件设计.研究结果表明,系统能满足实时性能要求,识别效果良好.     

一种新的变步长ICA自适应算法

结合互信息极小的优化判据，基于估计函数期望平方准则、外点法和最速下降法的思想，本文导出了一种新的变步长独立分量分析(ICA)自适应算法。该算法克服了固定步长在分离矩阵推导过程中出现的稳态失调问题，比基于模拟退火步长的ICA算法有更快的仞始收敛速度和较高的分离精度。同时，该算法还具有较好的时变系统跟踪能力。理论分析和仿真计算结果证实了其可以有效地提高ICA的自适虚性，更准确地完成盲信号分离。     

高维空间下求解MDA的扰动算法及其在人脸识别中的应用

本文提出了一种在高维空间下直接求MDA(Multiple discriminant analysis)最佳解的扰动算法，并把这一算法应用于人脸的识别中。在传统的MDA求解算法中，一般要求训练样本的个数足够大，以至于其类内散射矩阵为非奇异矩阵，即所谓的“小样本”问题。但是，在入脸识别中，由于人脸空间的维数非常大，而训练样本的个数有限，造成类内散射矩阵为奇异矩阵，从而使得用传统的求解方法失效。为了能在高维空间中求出MDA的最佳解，本文采用扰动的思想，巧妙地避开了矩阵的奇异性问题并找到了最佳变换矩阵。此外，把这一算法用于人脸的识别中，对ORL人脸图像库的实验显示，采用本文提出的算法达到比较低的错误率，其错误率仅为特征脸(Eigenface)方法的49．9％，为Fisher脸(Fisherface)的7914％。     

人脸识别研究进展

人脸识别技术在各种应用的推动下发展很快。而近几年中，为避免各种实际应用环境的限制，非约束环境下的人脸识别也得到了很大的发展。本文概述了人脸识别的一些主要方法，讨论了影响人脸识别的几个主要因素及其处理方法以及基于视频的人脸识别技术，最后指出了鲁棒的人脸识别技术的研究方向和发展前景。     

影响铁精矿K2O、Na2O、SiO2含量的因素分析

用统计分析方法 ,分析了影响精矿K2 O、Na2 O、SiO2 含量的因素 ,并根据分析结论提出了对生产工艺进行定向控制的条件     

Effects of stimulus emotionality and sentence generation on memory for words in adults with unilateral brain damage.

Does sentence generation and/or stimulus emotionality enhance verbal memory in patients with neurological impairment? This question was addressed by testing 40 patients with unilateral stroke (20 with left-brain and 20 with right-brain damage) and 20 healthy control participants for recall and recognition of 48 target words. During encoding, emotional and nonemotional words were either presented in sentences (read condition) or used to form sentences (generate condition). Both word emotionality and generative processing improved memory performance in all groups. The authors suggest that a similar influence (i.e., cognitive activation) underlies both of these memory-enhancing effects, although the putative origins of the 2 effects are quite different. Neuropsychological underpinnings and clinical implications of these phenomena are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Real-time control of video surveillance systems with program supervision techniques

In this article, we describe a knowledge-based controlled platform using program supervision techniques. This platform eases the creation and the configuration of video surveillance systems. Several issues need to be addressed to provide a correct system configuration: (1) to choose, among a library of programs, those which are best satisfying a given user request, (2) to assign a correct value for each program parameter, (3) to evaluate performances and to guarantee a performance rate which is satisfactory regarding end-user requirements. This platform is composed of three main components: the library of programs, the knowledge base and the control component. The knowledge is either given by experts or learnt by the system. The control is generic in the sense that it is independent of any application. To validate this platform, we have built and evaluated six video surveillance systems which are featured with three properties: adaptability, reliability and real-time processing.     

基于奇异值分解和神经网络的个性化信息模式识别

随着信息资源的持续增长，信息获取系统为特定用户提供特定信息服务的需求越来越重要。该文提出了基于奇异值分解和神经网络的个性化信息模式识别的方法，可以方便地获取用户信息需求的特征，并且利用这些特征信息完成个性化的信息识别和匹配，即实现个性化信息的模式识别，进而实现信息的个性化获取和管理。该文中的算法实现简单，可以方便地应用到目前的一些信息管理、服务系统中。