subroutine-3 802.15.4协议的实现

This is a code for periodic impusive noise in ofdm based power line communications. It is implemented in matlab.

说明：  基于矩阵特征值分解的功率谱估计包括特征向量估计和MUSIC估计，这两种估计方法均为非参数估计方法(Based on Eigenvalue Decomposition of power spectral estimation, including estimation and MUSIC eigenvector estimates, these two estimation methods are non-parameter estimation)

说明：  OFDM信道仿真源代码，基于matlab环境开发(OFDM channel simulation)

介绍了一中简单实用的图像数据融合程序,该程序运行快,融合结果优!(introduced a simple and practical image data fusion procedures, the procedures faster integration results were excellent!)

关于聚类问题的matlab程序以及其中函数的说明(clustering on the Matlab procedures and functions which the note)

Simulation for wireless sensor relaying network using DF model

说明：  T型三电平控制PMSM仿真，用于永磁同步电机控制，逆变器 三相逆变器 适合 在matlab环境下运行(PMSM simulation of T-type three-level control for permanent magnet synchronous motor control. Inverter three-phase inverters are suitable for operation in MATLAB environment.)

关野模糊模型 （也称为 TSK 模糊模型） 提出了高木、 关野和康在努力开发系统 从给定的输入输出数据集生成模糊规则的方法。这是 非常基本的例子，在 Matlab 具有一个输入与 4 会员 TSK 功能。它表明动态如何回传播算法收敛。

说明：  MATLAB编写的中值滤波函数，可用于一维数据的平滑处理。(The median filter function written in MATLAB can be used for smoothing one-dimensional data.)

matlab 关于association rule 的自己写的函数，有3个文件, association.m：h = association(m, i, j) i=>j, m是数据，h是support和confidence，该函数只适用于单个数据 ass_item: h=ass_itset(m, a, b) 同上，但是可用于多个数据（m为数组） assrule: h = assrule(m, threshold1, threshold2) 该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence (matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix) assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)