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MATLAB® is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. Using the MATLAB product, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran.You can use MATLAB in a wide range of applications, including signal and image processing, communications, control design, test and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes (collections of special-purpose MATLAB functions, available separately) extend the MATLAB environment to solve particular classes of problems in these application areas.MATLAB provides a number of features for documenting and sharing your work. You can integrate your MATLAB code with other languages and applications, and distribute your MATLAB algorithms and applications.

This code implement RBF neural network in matlab

用matlab实现的离散余弦编码，主要通过离散余弦编码的原理，用matlab实现的源代码。(Using matlab realize the discrete cosine coding, discrete cosine, mainly through the principle of encoding, using matlab realize the source code.)

PeMAQ16 error probability for 16qam modulation

Regression analysis using machine learning

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自适应阵列波束形成算法研究.kdh 硕士毕业论文(Adaptive array beamforming algorithm. Kdh Master' s Thesis)

快速计算一维信号的塔式谱峭度图，选择谱峭度最大值区间，方便确定所需滤波器中心频率及带宽。(Computes the fast kurtogram of signal x.This fast algorithm uses a pyramidal decomposition of the signal into a user-specified number of levels (a good choice is nlevel = 8). The first level is the classical kurtosis of the signal, the second level is the spectral kurtosis in 2 octaves, the third level the spectral kurtosis in 4 half-octaves, etc. Non-integer levels refer to divisions into third octaves. Here below is an illustration on how the frequency band is successively split when increasing the level)

DG Placement optimization in 33-bus and 69-bus distribution power systems using Imperialistic Competition optimization algorithm.

用MATLAB实现了基于pca的特征提取方法，有效地完成了识别，是识别的经典例子(Pca-based implementation using MATLAB feature extraction methods, efficient completion of the identification is to identify the classic example of)