xinhaofashejieshou0506

自己做设计用的参数提取程序，主要是LPCC和MFCC。(Designs its own program with the parameter extraction, mainly LPCC and MFCC.)

认知无线电中的波束成形MATLAB代码。可以根据拓扑众不同位置的节点调整天线的发射功率和角度。师兄博士毕业论文里的代码。希望能有帮助(Matlab code of beamformer in Cognitive Radio. it can regulate and adjust the transmitting power and angle of antenna, which belong my laboratory mate s PHD thesis. It may help you.)

jji计算直导线的电容的文档和matlab程序(jji capacitance calculation of straight wire matlab documentation and procedures)

异步电机仿真，查看电机性能的matlab仿真程序，希望对大家有所帮助(Induction motor simulation, see the electrical properties of matlab simulation program, I hope all of you to help)

数字图像处理及MATLAB实现（余成波）.pdf(Digital image processing and MATLAB to achieve (Yu-bo). Pdf)

包含了一个合成孔径雷达点目标回波模拟和R-D算法和一个距离参考函数(SAR RD imaging algorithm)

经典统计学 概率论基础,是学习MATLAB的经典手册(All of Statistics)

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)

本例用五点差分法求解一个二阶偏微分方程，其间用CG法处理，此实验可分别选取N=4，8，16，32(This example uses a five-point difference method for solving second order partial differential equations, during treatment with CG, were selected for this experiment can be N = 4,8,16,32)

在matlab中实现正切矫正程序,确定行、列中心点的位置。( tangent correction)