BP

对一幅被随机值冲击噪声污染的图像，用偏微分方法进行恢复，使用的模型是Total Varience(image restoration using TV model, remove random noise)

非线性整数规划图形工具 BNGUI Runs a GUI for BNB18 Usage: BNBGUI or BNBGUI(file) (Nonlinear integer programming graphical tools BNGUI Runs a GUI for BNB18 Usage: BNBGUI or BNBGUI (file))

多项式的曲线拟合，使用MATHCAD实现(Polynomial curve fitting using MATHCAD achieve)

用matlab做的单相boost PFC的仿真模型，功率11K，采用PI双闭环数字控制方法，波形较好。(Using matlab to do the simulation model of single-phase boost PFC power 11K PI double closed-loop digital control method, the waveform is better.)

matlab code for beging cc motor...

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. )

实例分析如何用GRADS实现NetCDF格式转换(Examples of how to achieve NetCDF format GRADS)

MATLAB库函数是非常有用的帮助资料，可以帮助初学者很快熟悉MATLAB的强大功能和应用范围。(MATLAB library function is very useful help information that can help beginners quickly become familiar with MATLAB' s power and range of applications.)

NW小世界网络的构成原则为：从一个环状的规则网络开始，网络含有N个结点，每个结点向与它最近邻的K个结点连出K条边，并满足N>>K>>In(N)>>1。随后进行随机化加边，以概率p在随机选取的一对节点之间加上一条边。其中，任意两个不同的节点之间至多只能有一条边，并且每一个节点都不能有边与自身相连。改变p值可以实现从最近邻耦合网络(p=0)向全局耦合网络(p=1)转变。在p足够小和N足够大时，NW小世界模型本质上等同于WS小世界模型。 (NW constitutive principles of small-world networks: from the rules of a ring network, network with N nodes, each node is connected to the K node with its nearest neighbor K edges, and meet N > > K > > In (N) > > 1. Followed by randomization into the plus side, with probability p with an edge between a pair of nodes in a randomly selected. Wherein between any two different nodes at most only one edge, and each node can not have a side connected with itself. P value can be changed to achieve the transition from the nearest neighbor coupling network (p = 0) coupled to the global network (p = 1). When p is small enough and large enough N, NW small-world model is essentially the same as the WS small-world model.)

FDTD贴片天线s参数，计算电磁场的数值方法教材(FDTD patch antenna s parameters, calculation of electromagnetic field of teaching methods)