USB_PIC_Prog

基于神经网络的遥感图像分类取得了较好的效果,但存在固有的过学习、易陷入局部极小等缺点.支持向量机机器学习方法,根据结构风险最小化(SRM)原理,表现出很多优于其他传统方法的性能,本研究的基于多类支持向量机分类器的遥感图像分类取得了达95.4 的分类精度.但由于遥感图像分类类别多,所需训练样本较大,人工选择效率较低,为此提出以人工选择初始聚类质心、C均值模糊聚类算法自动标注训练样本的基于多类支持向量机的半监督式遥感图像分类方法,期望能在获得适用的分类精度的基础上有效提高分类效率(Neural net based remote sensing image classification has obtained good results. But neural net has inherent flaws such as overfitting and local minimums. Support vector machine (SVM), which is based on Structural Risk Min- imization(SRM), has shown much better performance than most other existing machine learning methods. Using mul- ti-class SVM classifier high class rate of 95.4 is obtained. But for the class number of remote sensing image is much great, manually obtaining of training samples is a much time-consuming work. So a multi-class SVM based semi-super- vised approach is presented. It is choosed that the initial clustering centroids manually first, then label the samples as the training ones automatically with fuzzy clustering algorithm. It is believed that this method will upgrade the classifi- cation efficiency greatly with practicable class rate)

【实例简介】是一个子函数 可以分解接收信号为I路和Q路。

MySQL版本，压缩包中包含一个DDL和SQL文件，表结构字段如下：编码、名称、上级编码、名称简称、行政级别、地球坐标系WGS84,火星坐标系GCJ02、百度坐标系BD09；数据是目前最新的版本，取自国家统计局

说明：  bp神经网络预测电力负载，很好用~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(bp netural network applied in electricity prediction)

IPMI V2.0工作原理详解高性能、可靠的系统常常存在一个缺点：它们通常是利用具有很少或没有互操作性的专有部件生产的。过去，服务器管理依赖于专有工具，而专有工具管理多厂商服务器机柜和刀片服务器非常困难。人们需要一项标准将不同的东西整合在一起，这项标准就是“智能平台管理接口”(IPMI)。

一款swf播放器，对swf格式的文件，尤其是视频播放可以进行精确控制播放、暂停、快进等，swf大多是矢量格式，播放起来更是无损，新的福利

粒子群算法、遗传算法、动态规划等算法C#实现，貌似是那个学校做的

小波包分析提取振动信号中的特征频率，应用小区域方差对比，程序简单，真的是一个好程序。( Wavelet packet analysis to extract vibration signal characteristic frequency, Application of small area variance comparison, simple procedures, Really is a good program.)

基于MATLAB的语音信号特征分析描述，描述清楚，系统的描述了语音检测处理的方法，具有较高的参考价值。(The characteristics of speech signal analysis based on MATLAB description, clear description, system description method of speech detection processing, has high reference value. )

数据的逻辑结构、存储结构及它们之间的关系和相应的基本操作运算的定义和实现。 本书围绕数据结构的三种基本结构：线性结构（第2-5章）、树形结构（第6章）和图形结构（第7章）展开讨论，研究解决如下问题：一个具体问题的逻辑数据结构是什么？适宜选用什么样的存储结构？采用什么样的操作实现算法效率更高？ (Logical structure of data storage structure and the relationship between them and the corresponding basic operation and the realization of the definition of computing. The book data structure around three basic structure: a linear structure (the first chapter 2-5), tree-like structure (Chapter 6) and graphics structure (Chapter 7) initiate discussions to resolve the following issues: a specific problem What is the logic of the data structure? Suitable choice of what kind of storage structure? What kind of operation to achieve more efficient algorithm?)