计算齿轮箱阶次跟踪cotm2

徐政MMC柔直高速仿真资料word板，网上只有pdf版，很难得的资料。(Jones MMC soft straight high-speed simulation data word, only PDF version online, very rare.)

说明：  地震正演中面波模拟退火算法，该程序用来反演地层。(Surface wave simulated annealing algorithm in seismic forward modeling)

一个完整的可运行利用c++创建的GIS系统(A Complete Running GIS System Created by C++)

说明：  去混响的一个很好用的文件，在github上面下载的(To reverb a very useful file, downloaded from GitHub)

一个EJB教程-an EJB Guide

说明：  独立成分分析(Independent Component Analysis，ICA)是近年来提出的非常有效的数据分析工具，它主要用来从混合数据中提取出原始的独立信号。它作为信号分离的一种有效方法而受到广泛的关注。近几年出现了一种快速ICA算法(Fast ICA)，该算法是基于定点递推算法得到的，它对任何类型的数据都适用，同时它的存在对运用ICA分析高维的数据成为可能。又称固定点(Fixed-Point)算法，是由芬兰赫尔辛基大学Hyvärinen等人提出来的。是一种快速寻优迭代算法，与普通的神经网络算法不同的是这种算法采用了批处理的方式，即在每一步迭代中有大量的样本数据参与运算。但是从分布式并行处理的观点看该算法仍可称之为是一种神经网络算法。(Independent component analysis (ICA) is a very effective data analysis tool proposed in recent years. It is mainly used to extract the original independent signals from the mixed data. As an effective method of signal separation, it has been widely concerned. In recent years, a fast ICA algorithm (fast ICA) has appeared. The algorithm is based on the fixed-point recursive algorithm, which is applicable to any type of data. At the same time, its existence makes it possible to use ICA to analyze high-dimensional data. Also known as fixed-point algorithm, it was proposed by HYV & auml; rinen et al. It is a fast optimization iterative algorithm. Different from the common neural network algorithm, this algorithm adopts the way of batch processing, that is, there are a large number of sample data in each iteration. But from the point of view of distributed parallel processing, this algorithm can still be called a neural network algorithm.)

This a system of Telephone number rearch,it can easily tell you the area of the number

九宫格拼图游戏，基于VC++的拼图游戏，可智能打散图片，玩法，相信都知道怎么玩吧？点击空白处的图片到方块中，组合成一个完整的图片。游戏可适时显示游戏次数，自制的个性拼图，分享快乐。

界面编程的演示，窗口背景的渐变演示实例。(Programming interface presentation, the window shows examples of the background gradient)

这个文件主要介绍了LMS和RLS的一些基本的滤波功能-This paper mainly introduces the LMS and RLS some basic filtering