HMM_facerec

特征空间方法是现代谱估计的重要方法之一。针对噪声中的复正弦信号的模型，通过特征矢量的方法进行信号空间的分解。通过将信号空间分解为谐波信号空间和噪声信号空间这两个相互正交的空间的方法进行谱估计。Pisarenko,Music,ESPRIT算法都是这一类方法的重要算法。我们通过对不同算法进行比较分析不同算法在各种状况下的表现性能。并针对ESPRIT算法的各种改性和提升进行对比和测试。(Feature space is one of the modern spectral estimation method. Complex sinusoidal signal for the noise model, by the method of the feature vector for the decomposition of the signal space. By decomposition of the signal space to the space harmonic signal and the noise signal space, the method of the two mutually orthogonal spatial spectrum estimation. Pisarenko, MUSIC, ESPRIT algorithm is an important algorithm of this type of method. Different algorithms, our comparative analysis of the performance of different algorithms performance under a variety of conditions. And for a variety of modification and upgrading of the ESPRIT algorithm to compare and test.)

從網路取得關於自相關log-polar變換的實作。(Obtained from the network on the autocorrelation of the log-polar transform implementations.)

《Matlab7.x数字信号处理》源码，人民邮电出版社06年版，学习DSP算法很好的参考资料( Matlab7.x digital signal processing source, and the people s version of Posts )

结合matlab强大的数据处理能力和蒙特卡洛方法的强大随机模拟功能，编写了一个小算例(Matlab combination of powerful data-processing capabilities and a powerful Monte Carlo method of random simulation capabilities, to prepare a small example)

matlab编制的随机骨料多边形模型,适合随机骨料的建模和有限元分析(poly rabdom arrevege)

交叠最小干扰对齐算法，多用户干扰消除，有关求取最大特征值(The minimum overlap interference alignment algorithm, multi-user interference cancellation, related to strike the largest eigenvalues)

采用S函数写的多变量单神经元PID控制的SIMULINK仿真(NN PID CONTROLLER WRITED BY S FUNCTION)

an example c++ source code on how template is used

这个是用MATLAB写得 关于切比雪夫多项式展开的程序，输入一个函数 可以直接得到切比雪夫的展开时 很方便(This is written in MATLAB about the Chebyshev polynomial expansion program, enter a function can be very convenient Chebyshev expansion)

MATLAB计算机视觉与深度学习实战-运行视频(As a biological technology, face is difficult to be stolen and infection-free. In addition to that, it enjoys the authentication concealment and is never forgotten. Therefore, authentication based on face recognition will become the mainstream of future development. It has important and extensive application in various fields, and is also a hot topic at present biological characteristics identification technology research. Under the non-restrictive condition, the face recognition rate is not high, and its accuracy needs to be further improved. In this paper, the following aspects is analyzed)