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说明：  GMSK 信号在衰落信道中的频偏盲估计,学习阶段，大家共同进步(GMSK signal at the frequency of fading channel偏盲estimates, study phase, the common progress of U.S.)

考虑到传统的多示例多标签框架忽略了标签相关性，或者是将标签相关性作为全局概念知识加以利用，我们将局部标签相关性引入到MIML一SVM多示例多标签学习框架中来，得到了一种新的多示例多标签学习算法MIML LC SVM(Taking into account the traditional multi-sample multi-label framework ignores the label correlation or correlation between the label to be used as a global concept of knowledge, we will bow} local label correlation MIML into a multi-instance multi-label SVM learning framework in the past, get a new multi-instance multi-label learning algorithm MIML LC SVM)

直扩系统中的多径干扰信号的估计消除技术，通过仿真标量多径对直达信号的鉴相特性的影响。。(DSSS system multipath interference estimate signal cancellation technology, through the simulation of scalar multi-path of the direct signal phase characteristics. .)

对信道进行多种仿真，包括AWGN信道，信道参数，QAM映射方式和SFBC编码方式。(Of the channel to a variety of simulations, including the AWGN channel, channel parameters, QAM mapping method and SFBC encoding.)

苹果特征提取，按照灰度化，直方图均衡化，中值滤波，边缘检测，特征提取的顺序来 特征提取中，取得“比例系数”时，选择一张横径图片，序号与之前选择图像的相同(Apple feature extraction, according to grayscale, histogram equalization, median filtering, edge detection, feature extraction feature extraction in order to obtain " scale factor" , select a diameter of pictures, serial number and select the image before the same)

针对由于抖动和环境干扰造成的拍摄影像模糊问题，利用维纳滤波法进行图像恢复(As for the environmental disturbance caused by jitter and image blur shooting problems, the use of Wiener filtering method for image restoration)

This code will display a clock plot. this code is done in MATLAB.

多小区环境中channel gain的实现

matlab源程序，通过拉普拉斯变换进行两幅图像的融合，融合效果好(matlab source, through the Laplace transform fusion of the two images, good fusion effect)

计算统计手册采用matlab实现，书中详细介绍了数理统计的各种方法给出了对应的matlab程序，包括时下比较热门的非参数估计（PDF估计等）(There are wonderful books that cover many of the techniques in computational statistics and, in the course of this book, references will be made to many of them. However, there are very few books that have endeavored to forgo the theoretical underpinnings to present the methods and techniques in a manner immediately usable to the practitioner. The approach we take in this book is to make computational statistics accessible to a wide range of users and to provide an understanding of statistics from a computational point of view via algorithms applied to real applications.)