gaotv5

Matlab example for beginners(Matlab instance for beginners)

16QAM盲均衡,恒模算法，400次仿真，做出星座图，误差曲线(blind equalizaton for 16QAM,constant modulus algorithm，realization 400times ,constellation ,mmse curve)

power system load flow

pitch 的相关程序，自己编写的，可以条用，很好的，赶快下吧(pitch of the relevant procedures, their preparation, can be used, very good, quickly, are you)

Evolutionary Algorithms for Solving MultiObjective Problems第2版(Evolutionary Algorithms for Solving MultiObjective Problems)

传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这 一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表 示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的 语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优 于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method. )

图像配准技术，适合初学者，内部有解释说明，欢迎指正( Image registration techniques, suitable for beginners, internal explanation, please correct me)

《MATLAB R2008图形与动画编程实例教程》的源代码--第四章(" MATLAB R2008 examples of graphics and animation programming tutorial" source code- Chapter IV)

vanderpol 方程 的simulink模型仿真，参数mu,x10,x20设置不同参数。(van der Pol equation simulink model simulation, parameter mu, x10, x20 setting different parameters.)

可以用来计算分歧度，这个分析度是信息论中的一个概念，类似于熵。(we can use it to calculate the klsym divergence)