pca

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

内含结构拓扑优化的众多数学规划方法，其中包含最小二乘法、移动渐近线法等等(The file includes many methods for topology optimization，such as the method of moving asymptotes.)

var模型的实现。针对var模型的算法，估计模型的参数。并对其进行检验(achieve var model. Var model for the algorithm, the estimated parameters of the model. And its test)

基于均匀圆阵的信号二维方向角高精度估计 (Angular precision estimates based on two-dimensional uniform circular array signal direction)

TOA估计定位，采用固定门限法比较不同虚警下的估计性能。(TOA estimation location, using a fixed threshold estimation performance comparison of different methods under false alarm.)

可以得到很精确的幅值、频率、相位估计，相控阵天线的方向图（切比雪夫加权），matlab开发工具箱中的支持向量机，直线阵采用切比学夫加权控制主旁瓣比，滤波求和方式实现宽带波束形成，数据模型归一化，模态振动。( You can get a very accurate amplitude, frequency, phase estimation, Phased array antenna pattern (Chebyshev weights), matlab development toolbox support vector machine, Linear array using cut than learning laid upon the right control of the main sidelobe ratio, Filtering summation way broadband beamforming, Normalized data model, modal vibration.)

语音信号进行分析、处理和设计。用MATLAB做变声器的原理是通过改变输入声音频率，进而改变声音的音色、音调，使输出声音在感官上与原声音不同。变声器是借助对声音音色和音调的双重复合改变，实现输出声音的改变。通过自己发声，共振峰频率的改变是基于重采样实现的(Speech signal analysis, processing and design. MATLAB do voice-changer works by changing the input frequency of the sound, and then change the sound of the tone, pitch, so that the output audio with the original sound in different senses. Voice Changer is the use of sound timbre and tone of the dual composite changes, realize the output sound changes. Through their own sound, formant frequency change is implemented based on resampling)

there are two parts in these codes. the first implements an eight point algorithm which is used to compute the fundamental matrix in computer vision. the second is used to compute the optical flow and the unreliable region.

implementation of smoothening,laplacian and median filter.

MATLAB CODE FUNCTION CASCADE DETECT FACE AND RECOGNITION