MATLAB

channel estimation of combat pilot based technique, provides good estimation of ofdm channel

this matlab source code is basic

在matlab开发软件中，利用相关函数求两个信号的时间延迟。(In matlab software development, the use of correlation function of the two signals time delay.)

Matlab教案，通过理论和实际相结合的方式，详细介绍了matlab的编程方法(This file mainly focuses on the Matlab program design, which gives the theory and the example in the applications.)

Fuzzy c-means clustering (FCM) with spatial constraints (FCM_S) is an effective algorithm suitable for image segmentation. Its effectiveness contributes not only to introduction of fuzziness for belongingness of each pixel but also to exploitation of spatial contextual information. Although the contextual information can raise its insensitivity to noise to some extent, FCM_S (1) still lacks enough robustness to noise and outliers and (2) is not suitable for revealing non-Euclidean structure of the input data due to the use of Euclidean distance (L2 norm).

这是一个LDA主题模型的matlab代码，可进行中文模糊聚类分析，内涵说明，可直接使用。(This is a topic LDA model matlab code, can be Chinese fuzzy clustering analysis, meaning that can be used directly.)

续上一个程序的控制算法代码，非线性滑模变结构控制方法的程序，调试运行正确。(continuation of a process control algorithm code, nonlinear SMVSC control procedures, debugging and running correctly.)

说明：  相场模型的经典教程，包含MATLAB源代码说明，适合新手(the classic tutorial of Phase field modeling , including Matlab source code description, suitable for junior programmer)

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...)

这是一个用Matlab-S函数写的DFIG转矩程序(This is written in a Matlab-S function DFIG torque program)