NollogTest

基于中值滤波器的红外弱小目标检测，以9*9为滤波窗口大小(Median filter-based infrared small target detection, to 9* 9 for the filtering window size)

The attachment consists of a source code that performs malarial segmentation using k-means clustering.It also contains HUI conversion of an malarial image.Water shed algorithm applied on a cel image , and detection of water ridge lines for dental x ray image

说明：  e7力线通信中的部分关键技术研究，拿来分享下 (e7 power line communications in some of the key technical studies, brought to share the next)

关于matlab中的一些函数，以及对于函数的使用与说明(A document which is about the function in matlab)

用matlab来实现数字信号处理的原程序(using Matlab to digital signal processing to achieve the original program)

本程序用三边测量法来计算未知节点坐标且假设用于定位的锚节点位于等边三角形的三个顶点上。(This program uses trilateration to calculate the coordinates of unknown nodes and assume the anchor node for positioning in the equilateral triangle of three vertices.)

GM(1,1)模型1-4 1：GM(1,1)模拟模型，在matlab中的输入方法为gm1（x），x指要模拟的序列。 2：GM(1,1)预测模型，在matlab中的输入方法为gm2（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 3：GM(1,1)群模拟模型，在matlab中的输入方法为gm3（x），x指要模拟的序列。 4：GM(1,1)群预测模型，在matlab中的输入方法为gm4（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 gm4对序列趋势比较好的数据预测效果较好，对上下变动的数据，特别是后4个数据趋势跟前面的数据相反的，预测效果很差。 gm2对上下变动的数据，预测效果比gm4好，但对趋势较好的数据，预测精度没有gm4高。 gm3比gm1模拟精度要高。 可以以x=[1 3 5 7 9 11 13 15]进行实验。x输入默认行向量。 所有程序在matlab6.0上调试通过。(GM (1,1) 1-4 1 : GM (1,1) simulation model Matlab in the input method for gm1 (x), x entail simulation sequence. 2 : GM (1,1) model, in the Matlab input method for gm2 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. 3 : GM (1,1)- simulation model, in the Matlab input method for gm3 (x), x entail simulation sequence. 4 : GM (1,1)- forecasting model, in the Matlab input method for gm4 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. Gm4 right sequence relatively good trend data predicted better results, the next change in the data, especially after four data with the previous trend data contrary, predict poor. Gm2 next to the change in forecast resu)

cellular-d2d-caching

说明：  这些是对Matlab知识的一个总结，里面还有一些专题，比如优化问题，概率问题等等(This is a conclusion of Matlab knowledge. And you can also learn something else from this)

应用多元高斯声束叠加方法建立粉末合金构件的声场模型(sound field simulation sound field simulation sound field simulation )