yuvbmpfunction

codificacion huffman

This code develops dimensionless pressure, load carrying capacity, coefficient of friction, power loss, locations of maximum and terminating pressure for a finite width journal bearing. Parameters can be varied in the main file.

可靠性评估经典算例IEEErts96输入调用，matlab编程(Reliability evaluation classic example IEEErts96 input call, matlab programming)

跳频图案是跳频通信成功的基础，本代码计算了r=15时的m序列优选对，通过找到m序列的特征相位，模2得到了平衡Gold序列(Frequency hopping patterns is fundamental to the success of frequency-hopping communication, the code calculated the r = 15 when m sequence optimization right, by finding the characteristics of m sequence phase, mode 2 has been balanced Gold sequences)

k最近邻分类器。编写的一个matlab函数。输入向量Z表示所属的类，返回一个向量，表示由k最近邻分类给定的。(k nearest neighbor classifier. Write a matlab function. Input vector Z that belongs to the class, returns a vector, expressed by the k nearest neighbor classification given.)

粗糙集理论是一种基于对现实世界进行不确定描述的理论,属性约简是粗糙集理论的核心理论之一。对粗糙集理论进行阐述,并给出基于启发式的知识约简算法,最后结合MATLAB程序实例说明了该算法的可行性与有效性。(Rough set theory is based on the uncertainty of the real world is described in theory, attribute reduction is the core theory of rough set theory one. Elaborate on the rough set theory, and gives the knowledge-based heuristic reduction algorithm, and finally with MATLAB program example illustrates the feasibility and effectiveness of the algorithm.)

一级倒立摆的系统仿真动画，初始加速度为0，实现最基本的小车不动，摆杆动的仿真程序(An inverted pendulum system simulation animation, initial acceleration is 0, the most basic car does not move, moving pendulum simulation program)

使用支持向量机实现对数据的分类工作，精度很高，但是存在运行时间比较长的问题(The use of support vector machine implementation of the classification of data, high accuracy, but the existence of relatively long running time problem)

说明：  ：DBSCAN是一个基于密度的聚类算法。该算法将具有足够高密度的区域划分为簇，并可以在带有“噪声”的空间数 据库中发现任意形状的聚类。但DtLqCAN算法没有考虑非空间属性，且DBSCAN算法需扫描空间数据库中每个点的e一 邻域来寻找聚类，这使得DBSCAN算法的应用受到了一定的局限。文中提出了一种基于DBSCAN的算法，可以处理非空 间属性，同时又可以加快聚类的速度。(: DBSCAN is a density-based clustering algorithm. The algorithm has a sufficiently high density area is divided into clusters, and to be with the &quot noise&quot found in the spatial database clusters of arbitrary shape. But DtLqCAN algorithm did not consider non-spatial attributes, and spatial database DBSCAN algorithm to be scanned for each point e in the neighborhood to find a cluster, DBSCAN algorithm which makes the application subject to certain limitations. In this paper, an algorithm based on DBSCAN can handle the non-spatial attributes, can also speed up the clustering speed.)

Abstersiver 超强脱壳工具 很好用(Abstersiver powerful tools to good use Shelling)