基于多子空间线性判别分析的特征提取与分类

为了解决高维小样本数据的分类中Fisherface思想判别分析方法的不足,在最大散度差准则的基础上,提出了利用多线性子空间技术对每类样本进行单独描述的方法,该方法能更准确地反映样本在类内类间的分布关系.在分类中不是以距离作为判别依据,而是按照贝叶斯决策规则得到的隶属置信度作为衡量标准.实验结果表明了该方法的有效性,和同类方法相比,有更高的识别率.     

Online motion recognition using an accelerometer in a mobile device

This paper introduces a new method to implement a motion recognition process using a mobile phone fitted with an accelerometer. The data collected from the accelerometer are interpreted by means of a statistical study and machine learning algorithms in order to obtain a classification function. Then, that function is implemented in a mobile phone and online experiments are carried out. Experimental results show that this approach can be used to effectively recognize different human activities with a high-level accuracy.     

基于改进2DPCA的快速交通标志识别法

为了提高交通标志的识别速度,提出了一种样本类中间值结合均值的的2DPCA.该方法采用每类训练样本中间值的均值代替训练样本的平均值,以此重建散布矩阵从而得到最优投影矩阵.在已经建立的两个交通标志图像集上用该方法进行了实验,结果表明新方法识别速度得到了大幅提升并且取得了较高的识别率.     

Incorporating Ancestors' Influence in Genetic Algorithms

A new criterion of fitness evaluation for Genetic Algorithms is introduced where the fitness value of an individual is determined by considering its own fitness as well as those of its ancestors. Some guidelines for selecting the weighting coefficients for quantifying the importance to be given to the fitness of the individual and its ancestors are provided. This is done both heuristically and automatically under fixed and adaptive frameworks. The Schema Theorem corresponding to the proposed concept is derived. The effectiveness of this new methodology is demonstrated extensively on the problems of optimizing complex functions including a noisy one and selecting optimal neural network parameters.     

DHDECMP-TBP/OK萃取模拟高放废液中锕系元素的工艺研究

测定了22%DHDECMP 42%TBP/OK从模拟高放废液中萃取锕系元素的分配比;在微型离心萃取器(转鼓=10mm)串联台架上,进行了从模拟高放废液中萃取锕系元素的工艺条件研究。结果表明,经6级萃取、2级洗涤、6级反萃,流比AF∶AX∶AS=1∶1 5∶0 5,BF∶BX=1∶1时,在萃取器A中,U,Np,Pu,Am的回收率均大于99 9%;在反萃器B中,Am的反萃率>99 9%,U,Np和Pu的反萃率分别为2%,39%,2%。     

文本知识发现:基于信息抽取的文本挖掘蝌

In the general context of Knowledge Discovery, Knowledge Discovery in Text (KDT), which uses TextMining techniques to extract and induce hidden knowledge from unstructured text data, surges in the data and naturallanguage processing research. KDT is a multi-discipline of Artificial Intelligence, Machine learning, Natural Lan-ing with a stressing on its IE (Information Extraction)-based induction and specific sublanguage fields oriented prac-tices.     

汉语三字词声调的模式分析

汉语三字词的声调模式是复杂的。本文对4 男4 女各192 个三字词的声调进行分析,选择各音节的头尾差和相对调位比为特征,在进行特征抽取、统计和分析的基础上,研究了三字调整声调的模式和变调规则。本文的结果对三字词和连续语音声调的识别具有重要价值。     

Bayesian Landmark Learning for Mobile Robot Localization

To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optimality, since they rely on a human to determine what aspects of the sensor data to use in localization (e.g., what landmarks to use). This paper describes a learning algorithm, called BaLL, that enables mobile robots to learn what features/landmarks are best suited for localization, and also to train artificial neural networks for extracting them from the sensor data. A rigorous Bayesian analysis of probabilistic localization is presented, which produces a rational argument for evaluating features, for selecting them optimally, and for training the networks that approximate the optimal solution. In a systematic experimental study, BaLL outperforms two other recent approaches to mobile robot localization.     

一种融合PCA 和KFDA 的人脸识别方法

提出一种融合PCA和KFDA的人脸识别方法，即在进行非线性映射之前，首先利用经典的主分量分析(C—PCA)进行降维，然后执行KFDA．为进一步降低整个算法的计算时问，又提出一种I—PCA KFDA方法，它直接基于图像矩阵的主分量分析(I—PCA)．ORL标准人脸库的试验结果表明，与现有的核Fisher鉴别分析方法相比，两种方法可将特征抽取的速度分别提高3倍和7倍，其识别精度没有丝毫的降低．     

会展建筑中的大空间排烟系统分析

通过对会展建筑中的大空间展厅的火灾情形、排烟量及排烟方式的分析,得出了一个适合此类建筑的排烟系统设计的经济合理的参考方案.