FAST FEATURE RANKING AND ITS APPLICATION TO FACE RECOGNITION

A fast feature ranking algorithm for classification in the presence of high dimensionahty and small sample size is proposed. The basic idea is that the important features force the data points of the same class to maintain their intrinsic neighbor relations, whereas neighboring points of different classes are no longer to stick to one an- other. Applying this assumption, an optimization problem weighting each feature is derived. The algorithm does not involve the dense matrix eigen-decomposition which can be computationally expensive in time. Extensive exper- iments are conducted to validate the significance of selected features using the Yale, Extended YaleB and PIE data- sets. The thorough evaluation shows that, using one-nearest neighbor classifier, the recognition rates using 100-- 500 leading features selected by the algorithm distinctively outperform those with features selected by the baseline feature selection algorithms, while using support vector machine features selected by the algorithm show less prominent improvement. Moreover, the experiments demonstrate that the proposed algorithm is particularly effi- cient for multi-class face recognition problem.     

弹丸超声速绕流的Navier-Stokes模拟

本文轴对称Ｎａｖｉｅｒ－Ｓｔｏｋｅｓ方程组出发，采用高分辨率对称ＴＶＤ格式数据模拟了包括底部回流区在内的弹丸超声速绕流流场。     

破译空气密码的701秘密基地

"701"是一个神秘单位的名字。就像电视连续剧《暗算》里的701所是一个严格保密的研究所一样,航天701所也是一个密级很高的专业研究所,只不过它的研究内容不是破译密码,而是破译空气对于航天器的秘密作用。1956年12月,这个秘密基地在北京西南郊的西山脚下、牤牛河畔诞生,它标志着中国航天空气动力学研究的开端。     

破译空气密码的701秘密基地

“701”是一个神秘单位的名字。就像电视连续剧《暗算》里的701所是一个严格保密的研究所一样，航天701所也是一个密级很高的专业研究所，只不过它的研究内容不是破译密码，而是破译空气对于航天器的秘密作用。