boilerdigital

使用线性回归的方法进行预测、训练，适合初学者使用(Using linear regression method to predict training for beginners)

A simple test of RS232 communication between a computer and a surgical light dimmer

Bluetooth is a wireless technology that allows computers, phones, headsets, PDA s and other devices to wirelessly communicate over short distances (up to 33 feet). Bluetooth uses radio waves (in the 2.4 GHz range), and is designed to be a secure, low power and inexpensive way of connecting and exchanging information between devices without the need for wires or cables to link devices together.

实在不怎么会了，这都是我一学期来，老师教的一些了(I m a new student)

自己建立的iclark变换模块，根据TI公司永磁电动机例程编写(iclark tansform created by myself, based on TI s permanent magnet motor routines)

GMM模型和贝叶斯分类器 用于视频图像的处理(GMM model and the Bayesian classifier for video image processing)

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))

cross correlation of two sequences

this code for add training sequence in OFDM system

Implements Maximum likelihood estimation of beta and other parameters for model of stock portfolio vs. index using kalman filter