crazyflie

SC-FDMA, which is used in the uplink transmitter side in LTE

能够很好的实现hilbert变化，结果和matlab基本一样，已经通过实验。(Hilbert can achieve very good changes, results and basic matlab, as the experiment has passed.)

人工蜂群算法(ABC)的matlab代码,外国人做得,求解连续函数问题(Artificial bee colony algorithm (ABC) matlab code, foreigners do, problem solving continuous function)

实现矩阵的LU最大主元分解，方便快捷有效，可以查看分解过程，适合初学者(Achieve maximum principal component matrix LU decomposition, convenient and effective, you can view the decomposition process, suitable for beginners)

说明：  人工势场法程序代码，用matlab编写，简单易懂(the code,you can use it to set the obstale imformation ,the length and so on)

particle filter learning for target tracking applications

对于一幅输入图像，将产生一幅输出图像，输出图像的每个像素点的灰度值由输入像素点决定，将感兴趣特征的对比度扩展使之占据可显示灰度级的更大部分。使一输入图像转换为在每一灰度级上都有相同的像素点数，均衡化会减少灰度级数。大多数自然图像由于其灰度值分布集中在较窄的范围之内，引起图像细节不够清楚。采用直方图修正后可使图像的灰度间距拉大或使灰度均匀分布，从而增大了反差，使图像细节清楚，达到增强的目的。(For an input image, will produce an output image, the output image gray value of each pixel from the input pixel decided to expand interest in the contrast of features to make it account for more gray levels can be displayed most. Make an input image is converted to grayscale in each pixel have the same points, equalization will reduce the gray series. Most natural images because of their gray value distribution concentrated in a narrow range, causing the image detail is not clear enough. Make the image histogram revised by the gray space widening or so gray uniform distribution, thereby increasing the contrast between the image details clear objective to achieve enhanced.)

基于matlab的SOM神经网络源码,讲解matlab下如何实现SOM神经网络，给出实例(SOM—ANN source code based on matlab)

bpsk加噪和不加噪情况下最佳相干解调的编解码。(The BPSK adding noise and without noise coherent demodulation codec.)

一种用于判决反馈均衡器的方法和装置，其中使用一校正项来补偿限制器误差，从而避免了误差传播。选择均衡器的滤波器系数以便使均衡器的代价函数最小(One for decision feedback equalizer method and device, which uses an error correction terms to compensate for the limiter, thus avoiding error propagation. Select equalizer equalizer filter coefficients so that the minimum cost function)