PSO-algorithm-in-matlab

图像传输过程中，经常会受到各种噪声的干扰，本程序采用邻域平均法来减少噪声(In the process of image transmission, there will be various noise interference always,this program is to reduce noise base on Neighborhood average method. )

详细介绍了用迭代法求解线性方程组的方法及其Matlab语言表示。(Iterative method described in detail with the method for solving linear equations and Matlab language said.)

王正林-<精通matlab科学计算>电子书,适合matlab初学者(Wangzheng Lin- <proficient matlab scientific computing> e-books for beginners matlab)

In BPSK modulation, the phase of the RF carrier is shifted 180 degrees in accordance with a digital bit stream. A form of phase modulation in which the modulating function shifts the instantaneous phase of the modulated wave between predetermined discrete values. Abbreviated PSK

Matlab有限元分析与应用，很好很重要(Matlab finite element analysis and applications, very good is very important)

Matlab file okumura models

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

写入for3d程序需要的in文件，此例是以具体应用中的具体问题而写。(also a programme that product the infile of for3d programme.)

SUSAN算法，包括去除伪角点的方法，重心，非极大值抑制(SUSAN algorithm, including the method of removing false corners)

用MATLAB实现的压缩传感，雅克比迭代求解线性方程组课设,时间序列数据分析中的梅林变换工具。( Using MATLAB compressed sensing, Jacobi iteration for solving linear equations class-based, Time series data analysis Mellin transform tool.)