Advanced-Mathematics-Matlab

EA名称：套利精灵 EA类型：对冲套利 一、功能介绍 本EA遵行顺大势，逆小势策略入场交易； 二、核心优势 多货币套利，对冲风险获取盈利，每月有一次机会单局最大利润达到30% 三、注意事项 （1）如适用周期：该EA只须在欧美一分钟图表上，就能运行多对货币。 （2）资金要求：建议3000美金，最少入金不少于1000美金 （3）时间段：全时段，正常情况无需人工干预，在盈利的情况下，可视情况自行平仓;(EA Name: Arbitrage Elf EA Type: Hedging Arbitrage I. Introduction of Functions This EA follows the general trend and counter-minor strategy to enter the market. II. Core Advantages Multi-currency arbitrage, hedging risk for profit, once a month, the maximum profit of a single board reached 30%. Notes (1) If applicable: the EA can run multiple pairs of currencies only on a one-minute chart in Europe and the United States. (2) Capital requirements: Recommend $3000, at least $1000 (3) Time period: Full-time period, normal conditions without manual intervention, in the case of profit, according to the circumstances of self-liquidation;)

ov7670 arduino based library

常见的buffer设计，包括：Fast ring buffer, Loop buffer, Bip buffer， circular character buffer，可以方便的集成到相关代码中(common buffer example and code, including fast ring buffer, loop buffer, bip buffer, circular character buffer, and they can integrate to relative code easily.)

使用hough变换检测直线的matlab程序(Detect the use of straight line hough transform matlab program)

第5个：matlab 和C++联合用于SVM，另外一种风格的(the 5 file: matlab and c++ together for SVM)

说明：  可在matlab中运行，是通过matlab读取视频的有效软件(Run in matlab, matlab read through the effective video software)

paper for research science

c++实现农夫过河问题，包含全部代码，实现过程，问题分析(c++ to achieve the farmer across the river issues, including all the code, the implementation process, problem analysis)

用C语言 和 c++编写的卡尔曼滤波 有着详细的代码和方法 希望能帮助到你们(Written in C and C++ the kalman filter has detailed code and method can help to you hope )

LLE算法基于swiss roll与s-curve数据集的运行结果，选取的样本点数为N=2000、k=12、 d=2进行的降维运算的结果,由运算结果可知在不同的数据集上LLE算法依然能够很好地保持数据在降维前后结构的特点。(The LLE algorithm is based on the running results of Swiss Roll and S-curve data sets, and the number of selected sample points is the result of dimensionality reduction of N=2000, k=12 and d=2. It is known that LLE algorithm still can maintain the characteristics of the data before and after dimensionality reduction well on different data sets.)