ServoDcmotormodel

ALPS folder 2. generate_matrix.m: generates measurement matrix. 3. generate_vector.m: generates sparse vector. 4. Report_bibtex.tex: bibtex reference for citing. 5. ALPSdemo.m: demo of ALPS.

matlab 教程。。。对于没用过matlab的 可以作为入门学习(matlab tutorial. . . For matlab can not used as a learning portal)

利用有限差分算法实现动力学方程的求解单个球体在环形容器中运动分析(Finite difference algorithm for solving the dynamic equations in a single sphere in the circular movement of the container)

里面包含五个有关matlab的学习的资料，特别适合初学者使用。(a very good learning material of matlab learning.)

主元分析（PCA）的Matlab源代码分析(source code of PCA runed on Matlab)

说明：  空间直角坐标转换，BURSA模型解算七参数(Transformation of space rectangular coordinate and solution of seven parameters with bursa model)

基于MATLAB的双音多频信号DTMF的生成。(MATLAB-based dual-tone multi-frequency DTMF signal generation.)

matlab code for MAC Layer to simulate and verify resultat

永磁电机仿真！！(PMSM control!!!!)

Finally, probability analysis, based on the chosen database, is performed and judgment whether the person is recognized is pronounced. Two different modeling techniques can be suggested for purposes of person identification or verification. The approach based on Hidden Markov Speaker Models (HMMs) with the mixtures of Gaussian distribution is text-dependent one. For this technology a speaker is described by a set of HMMs, constructing the set of speech groups spoken by that person. The speech groups may be phonemes or words [7]. The text-independent technology is rested upon Gaussian Mixture Speaker Models. For this technology each speaker is defined by only one model describing all utterances of that person. Identification in the range of both approaches is executed by evaluation of maximum a posteriori probability [7].