DSDP5.8WIN

说明：  使用粒子群算法解决10个城市的旅行商问题 可绘制图形(Use the particle swarm algorithm to solve traveling salesman problem of 10 cities can draw pictures)

这5个小程序分别为：用Monte Carlo随机法圆柱相交体的体积；用刘徽割圆法计算pi；梯形法.辛普森法计算圆周率；蒲丰掷针实验程序；线性函数的迭代(This five small programs were: using Monte Carlo random method cylinder intersects the volume cyclotomic method with Liu Hui pi trapezoidal method Simpson method to calculate pi Buffon throw needles experimental procedures linear function of iteration)

Spectral analysis of discrete deterministic signals

Matlab小波变换与傅立叶变换用于检测阶跃信号，原始时域信号是一个阶跃信号，为了确定阶跃信号的突变点，分别采用傅立叶变换和db5小波进行处理。(Matlab wavelet transformation and Fourier transform is used to test signal, the original order jump time signal is a step road signal, in order to determine the Laplace domain signals point mutations, respectively the Fourier transform and db5 wavelet for processing. )

FET5X IS A PACKAGE FOR DOING DGSE MODEL

说明：  一种未知信源数的高分辨DOA 估计算法：众多性能优良的超分辨波达方向(DOA)估计算法通常需要预先判定信源数目，然而，现有的信源数估计 算法在有限采样快拍条件下，估计性能随着信噪比的降低而下降，错误概率也相应增加，最终导致DOA 估计失败。 该文提出一种超分辨的DOA 估计算法，此算法不需要预判信源个数和进行特征值分解，同时在时变环境中，针对 快拍数较少的情况下，依然保持较高的角度分辨能力，可以被认为是综合了Capon 法和MUSIC 法的优点。(Algorithm on High Resolution DOA Estimation without Sources Number：Many of the super resolution DOA(Direction-Of-Arrival) estimation algorithms presume the number of signal sources. Since the sample snapshot is limited, however, the available algorithms on source number estimation may fail at lower SNR. In this paper, a novel algorithm for high resolution DOA estimation is proposed, which not only skips sources number estimation and EVD, but also behaves satisfactorily with a few snapshot, it may be viewed as a combination of merit of conventional Capon and MUSIC method.)

基于端点检测的谱减法语音增强，语音的去噪算法仿真程序，可以进一步改进(Endpoint detection of the spectral subtraction based speech enhancement)

TigerSharc TS201 floating point lms filter routine(TigerSharc TS-201 floating point lms filte r routine)

很好的程序！Lu系统的Lyapunov指数，分岔图和庞加莱映射！(Good program! Lyapunov index, bifurcation diagram and Poincare map of Lu system.)

本程序是针对UCI图像数据集上的图像进行重构与识别的实验(This procedure is for the UCI data sets on the image to reconstruct the image and recognition of the experiment)