CSL1.0

本文利用软件相移技术得到相互正交的参考正弦波信号；通过互相关算法，完成了软正交矢量型LIA相关器的具体实现；利用该方法实现了对微弱信号幅值和相位的检测，有效地抑制干扰，减少了硬件电路成本。通过Matlab仿真，验证了该算法具有一定的优越性。(In this paper, the software technology is orthogonal to the phase shift of the reference sine wave signal through cross-correlation algorithm to complete the implementation of soft orthogonal vector LIA correlator achieved using this method for detecting a weak signal amplitude and phase, effectively suppress the interference and reduce the cost of the hardware circuit. By Matlab simulation show that the algorithm has certain advantages.)

此算法是基于小波变换模极大的多尺度图像边缘检测(this algorithm is based on the wavelet transform modulus maxima Multiscale Edge Detection)

a bunch of useful functions for image reconstruction

这是根据《最优阵列处理技术》一书中，第三章零点调向编写的代码。是自己写的。比网上给出的那个随书附带例程要详细。并且在关键的地方附加了注释。各位刚开始看这个比较迷茫的可以参考(failed to translate)

正弦波叠加方法产生clark参考模型 参考文献Second-order statistics of an improved jakes fading simulation(Second-order statistics of an improved jakes fading simulation)

A Predictive Functional Control Demo.

遗传算法优化后计算潮流的一个改进程序，给大家看看(Genetic algorithm optimization of a trend of improvement after the calculation procedure for everyone to see)

用于matlab的lrm算法，一个不错的例子(an example of LRM algorithm)

％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％( EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates)

国外最新的有关MATLAB方面的电子书籍，值得一读，推荐！(good book.)