fastkmeans

使用下面的参数设计信道均衡器，其中使用两个独立的随机数发生器，一个用x(n)来表示，用来测试信道；另一个用v(n)来表示，用来模拟接收器中的加性白噪声的影响。序列x(n)是x(n)=±1的伯努利序列，随机变量x(n)具有零均值和单位方差。第二个序列v(n)具有零均值，其方差由信噪比决定。均衡器有11个抽头。(Use the following parameter design of channel equalizer, which uses two separate random number generator, one with x (n) to indicate, to test the channel the other with v (n) to indicate to simulate the receiver in The additive white noise. Sequence x (n) is x (n) = ± 1 of the Bernoulli sequence of random variable x (n) with zero mean and unit variance. The second sequence v (n) has zero mean, its variance decision by the signal to noise ratio. There are 11-tap equalizer.)

ber_ldpc G(F)non bariny LDPC code

SIMCA(簇类的独立软模式方法）-MATLAB代码 聚类分析包括举例。(Data cluster analysis)

说明：  从图像经灰度级压缩，计算灰度共生矩阵，提取纹理特征参数，包括有能量，熵，惯性矩，对比度，相关度。算法包含有matlab封装函数计算方式，以及自行变成计算方式，两种纹理特征提取算法。(Gray level compression is used to calculate gray level co-occurrence matrix and extract texture feature parameters, including energy, entropy, moment of inertia, contrast and correlation. The algorithm includes two kinds of texture feature extraction algorithms: matlab encapsulation function calculation method and self-transformation calculation method.)

(书)现代通信系统使用MATLAB第四章(ALLIANCES is a recently proposed cooperative random access protocol for wireless networks. In this paper we modify the original model to include user location information. We also derive pair-wise error probability (PEP) under Rayleigh flat fading channel and a power-law attenuation environment. Based on the PEP analysis we propose an optimal relay selection scheme, which achieves significant throughput gains as compared to the random relay selection scheme in the original ALLIANCES.)

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

霍普菲尔德网络的另外一个例子，matlab编程(Hopfield networks, another example, matlab programming)

这个包包括了一个多类代价敏感学习方法Rescalenew。这是一个通用的方法,如instance-weighting, sampling, threshold-moving等。(This package includes a multi-class cost-sensitive learning method Rescalenew. This is a general method which can be realized in many ways such as instance-weighting, sampling, threshold-moving, etc. This package includes five implementations of the method, that is, instance-weighting+C4.5, over-sampling+C4.5, under-sampling+C4.5, threshold-moving+NN and threshold-moving+PETs (probability estimation trees). )

利用matlab编程实现偏最小二乘算法，可完成辨识模型的参数(partial least square)

SAR RD算法 亲测可用 解压使用matlab打开运行即可 效果很好(SAR RD decompression algorithm using matlab pro-test available to good effect to open the Run)