pso1

Fixed-Point iteration(Function fixed_point(p0, N) approximates the solution of an equation f(x) = 0, rewritten in the form x = g(x), which is a sub-function the user has to enter. the call to the function fixed_point(p0, N) returns the root of the equation f(x),i.e. the fixed-point of g(x), if the procedure is successful or a sequence of iterates in case something goes wrong. p0 is the initial approximation and N the maximum number of iterations. If, after N iterations, condition |x(k)- x(k-1)| < tol is not satisfied, all iterated values will be displayed, accompanied by a message asking the user to either change p0 in case of divergence or enter another g(x) that does not lead to complex numbers arithmetics. Reasons for the program to go wrong are the divergence of iterates and/or appearance of complex numbers for example with functions involving sqrt(x) when one of the iterates is negative. )

matlab中fft数字通信源程序的实现(fft in matlab source code implementation of digital communication)

统计稀疏分解（SSDP）欠定盲分离MATLAB仿真程序。能在接收天线个数小于源信号个数时，仅仅利用观察信号恢复出源信号。(Statistics sparse decomposition (SSDP) underdetermined blind separation of MATLAB simulation program. In the number of receiving antennas is less than the number of source signals, using only the observed signal to recover the source signals.)

dcsk差分混沌相移键控 混沌调制解调 混沌信号生成 高斯噪声(dcsk chaos modulation awgn)

一个图像增强程序，用MATLAB编写，针对过曝光和欠曝光，方法简单。(An method for underexposed image processing.)

bidirectional elm matlab code

This is the IEEE paper as the research in the matlab platform its very important for student research project

说明：  这个是基于非测距无线传感器网络定位算法的仿真(This is based on the non-distance localization algorithm in wireless sensor network simulation)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)

ant colony algorithm for tsp calculate the shortest path between differnt cities. traveler pass from any city onr time