2-_-Basic-Lattice-Boltzmann-(LB)

EM算法，基于期望最大化原则进行密度估计(EM algorithm, based on the expectation maximization of the principle of density estimation)

对自适应滤波器和卡尔曼滤波器用MATLAB对语音信号进行了滤波，发现卡尔曼滤波器能够在较大的噪声中还原原来的信号。(Kalman filtering)

阵列信号用LCMV算法得到的波束形成，和图像(With LCMV algorithm are array signal beam-forming, and image )

一维等离子体FDTD的Matlab源代码，计算电磁学方向(One-dimensional plasma FDTD Matlab source code, computational electromagnetics direction)

编写一个可以增强图像的函数，可以使得图像的灰度级转变。(Write a function that can enhance the image, you can make changes in the gray level of the image.)

CHAN算法的仿真源代码.条件为基站三到七个.服从高斯分布,无非视距传播.... (CHAN simulation algorithm source code. Conditions for the base station 3-7. Obey the Gaussian distribution, the spread of no more than line-of-sight ....)

相位编码脉冲压缩雷达的多普勒补偿偿算法，实现对信号的补充可直接使用。 (Phase-coded pulse compression radar, Doppler compensation compensation algorithm, to supplement the signal can be used directly.)

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)

this file contains prtools (pattern recognition tools).

this function is getting the background by mean function for rael time . the function calc the mean of every pixel .