MBC

说明：  详细讲解了MATLAB语言编程技术，有大量的实例。(Detailed account of MATLAB programming language, there are plenty of examples.)

matlab无约束优化问题的信赖域算法程序-matlab trust region method(matlab trust region method matlab trust region method matlab trust region method)

关于OSTBC的天线选择，采用天线选择的Alamouti STBC方案，比较BER性能，由仿真图能得出天线选择方法能够提供比预编码更多的增益。(About OSTBC antenna selection, antenna selection scheme using Alamouti STBC, compare the BER performance, can be reached by a simulation diagram antenna selection method can provide more than pre-coding gain.)

In this file you can find a simple but very effective algorithm for Nearest Neighbour Search which I megalomaniacly called the GLTree.

LDPC码的完整的编译码，关于神经网络控制，一个很有用的程序。( Complete codec LDPC code, On neural network control, A very useful program.)

实现偏最小二乘建模以及模型优度计算。应用于数据分析。(Partial least squares modeling and model optimization are implemented.)

利用小波分解与重构,实现图像去噪和压缩,可灵活选用其他小波,简单易懂,特别适合小波初学者.(using wavelet decomposition and reconstruction, Image Denoising and Compression, the flexibility to choose other wavelet is simple to understand and Wavelet particularly suitable for beginners.)

Elnagar, G., et al. (1995). "The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40(10). 上述文章的算例2的仿真代码(Elnagar, G., et al. (1995). " The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40 (10). the simulation code of example 2 in the preceding article.)

盲源分离；求峭度；可以把混合信号分离出来，并且可以比较前后分离信号的峭度(Blind source separation seek kurtosis can separate the mixed signal, and the signal can be compared before and after the separation of kurtosis)

K-SVD可以看做K-means的一种泛化形式，K-means算法总每个信号量只能用一个原子来近似表示，而K-SVD中每个信号是用多个原子的线性组合来表示的。 K-SVD通过构建字典来对数据进行稀疏表示，经常用于图像压缩、编码、分类等应用。(K-SVD can be regarded as a generalized form of K-means. The total K-means algorithm can only approximate one signal for each semaphore, and each signal in K-SVD is a linear combination of multiple atoms To express. K-SVD through the construction of the dictionary to sparse data representation, often used for image compression, encoding, classification and other applications.)