Chaos-particle-swarm

S-G滤波器，可实现较好的噪声滤除功能。(S-G filter which can achieve better in denoising stochastic noise.)

求波形的峰值，可以求出一组数据中的峰值，并且数据的峰值可以有很多个。(Seeking the peak of a waveform, can be calculated in a set of data in the peak, and the data of the peak there can be many。)

nearestSPD works on any matrix, and it is reasonably fast. As a test, randn generates a matrix that is not symmetric nor is it at all positive definite in general.

This algorithm is ADI algorithm.

全向阵元和有向阵元的模式空间图，有助力于理解宽带波束形成(the mode pattern of ominidirectional array elements and directional array, it is helpful to understand the broadband beamforming)

对鸟鸣信号和脉冲信号进行傅里叶变换并相乘，实现卷积功能(Birdsong signal and the pulse signal, the Fourier transform and multiplying the convolution function)

摘　要:针对茄子图像的灰度和颜色特点,利用MATLAB中丰富的图像处理函数,分别进行了色差分割和色调分割。在 色调分割中,采用了自动选取阈值的Otsu法。在去除残留噪音的处理中,采用标注的方法对二值图像的各连通区域进行面积 统计。保留最大面积的区域,从而使分割效果大大改善。利用多参数来衡量分割效果,使评价做到最大程度的客观、合理。(Based on the gray- level and color characteristics of eggp lant image, hue and color- difference segmentation were conducted by using the rich image p rocessing functions embedded inMATLAB. The auto threshold- adap tivemethod ofOtsu operation was specially used for hue segmentation. And upon the elimination of the residue noise, labelingmethod for statistical calculation was introduced for the connected regions of the binary image. Themaximum areaswere p reserved to imp rove segmentation effects. In addi2 tion, multi- indiceswere app lied to assess the effect of segmentation, in order to get impersonal and reasonable assessment)

说明：  用MATLAB做的地面动目标检测，通过杂波抑制，dcpa等等相位中心天线技术，来检测出地面的动目标。(this code is the result of the code ,in fact ,it is the result of the code ,it is using the radar to detect the moveing targets in the ground ,that is it.)

EMD方法，可将非平稳信号降解为单频信号。用于分析其频谱特性。(EMD method, the non-stationary signal degradation for single-frequency signal. For the analysis of their spectral characteristics.)

解决大规模限量弧路由的程序，本程序采用了PAM聚类的方法。(To solve large-scale limited arc routing procedures, the program uses a PAM clustering method.)