power_hvdc12pulse

微信定位源代码,微信定位精灵,定位助手,微信定位软件(Micro-channel positioning source code, micro-channel positioning elves, positioning aides, micro-channel positioning software)

说明：  短波信道watterson模型的建模仿真，已经编译通过。(The simulation of Watterson model of HF channel has been compiled.)

mathematic全美经典教程，中文版本，非常实用。(mathematic language tutorials, Chinese)

常规地震假设地下介质是各项同性的，但实际上，是各向异性的。各向异性介质的反射系数随入射角、方位角不同而不同。(Reflection coefficient varies with incident angle and azimuthal angle.)

障碍物的源程序m文件，能在matlab中成功运行(The source program m file of the obstacle can successfully run in matlab)

对图像进行直方图均衡的matlab程序示例。里面有图像处理前后直方图对比，代码简单易懂。(Histogram equalization)

system for recognition of fingerprint

matlab下利用元胞自动机进行细菌生长模拟，具有一定的学习价值(matlab under utilization of cellular automata for bacterial growth simulation, has a certain value of learning)

通信原理基于Matlab的计算机仿真,书籍电子版和源代码完全版。 作 者：郭文彬 出 版 社：北京邮电大学出版社 出版日期：2006-6-1 内容简介 本书主要针对《通信原理》这门课程，通过实例详细讲解了利用Matlab进行信真的方法。书中给出了大量的Matlab脚文本文件和范例。通过计算机模拟与仿真，一方面能使读者加深对所学基本理论的理解；另一方面，使读者能迅速掌握Matlab进行通信系统仿真的技巧。 全书共10章，包括：Matlab基本知识、确定信号分析、随机过程、模拟调制、数字频带传输、模拟信号的数字化及编码、信道及信道容量、扩频通信与伪随机序列等内容。(Communication Theory full version of Matlab-based computer simulation, books, electronics, and source code. Adds Kuo: Press: Beijing University of Posts and Telecommunications Publishing Date :2006-6-1 Introduction book focused on " Communication Theory course through examples explain in detail the method of to using Matlab letter really. The book gives a lot of the Matlab the pin text file and example. Through computer modeling and simulation, which would enable readers to deepen the understanding of the basic theory On the other hand, so that readers can quickly grasp Matlab communication system simulation techniques. The book is 10 chapters, including: Matlab basic knowledge to determine the signal analysis, stochastic processes, analog modulation, digital band transmission, the analog signal is digitized and coding, channel and channel capacity, spread spectrum communication with pseudo-random sequences.)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)