workuse

QAM的MATLAB演示. 图形演示，很好的教学范例. 很适合于初学者.(QAM demo of MATLAB. Graphic presentations, examples of good teaching. Very suitable for beginners.)

说明：  reg 转换为 hsv 的matlab源代码 subplot(221) subimage(ph) colorbar xlabel( (a)色调分量图像 ) subplot(222) subimage(ps) colorbar xlabel( (b)饱和度分量图像 ) subplot(223) subimage(pv) colorbar xlabel( (c)亮度分量图像 ) subplot(224) subimage(phsv) colorbar xlabel( (d)调整后的图像 ) (reg into the matlab source code hsv subplot (221) subimage (ph) colorbar xlabel (' (a) color component image' ) subplot (222) subimage (ps) colorbar xlabel (' (b) saturation component image ' ) subplot (223) subimage (pv) colorbar xlabel (' (c) luminance component image ' ) subplot (224) subimage (phsv) colorbar xlabel (' (d) Adjustment After the image ' ) )

计算信噪比，计算公式是信号能量比上噪声能量(SNR Calculation，signal power divide noise power)

基于遗传交叉算法的改进的混沌粒子群优化算法。(The improved chaotic particle swarm optimization algorithm based on genetic crossover algorithm has high convergence speed and high precision)

关于cdma系统的rake接收机的仿真，希望对大家又所帮助。(On the rake receiver cdma system simulation, and they hope to also help everyone.)

一些简单的入门教程，易懂易上手。简单的阐述方式，可使读者尽快掌握要领。(Some simple introductory tutorial, easy to understand the difficulty of use.A simple exposition of way, will enable readers to quickly grasp the essentials.)

说明：  环搜法搜索目标的数学模型和仿真程序，并绘制最终的轨迹图(Central Law search found mathematical models and simulation procedures, and draw the ultimate locus)

说明：  LPI和LPID的主要目的是能够在比截获接收机对雷达进行探测与干扰的距离更远的距离上来探测目标,本工具箱是在MATLAB下的LPI工具箱(LPI and LPID' s main purpose is to intercept receiver than the radar detection and jamming on the distance farther up exploration goals, the toolkit is under the LPI in the MATLAB Toolbox)

通过虚拟阵元进行DOA估计，非归零型差分相位调制信号建模与仿真分析 ，用谱方法计算流体力学一些流动现象的整体稳定性。( Conducted through virtual array DOA estimation, NRZ type differential phase modulation signal modeling and simulation analysis, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon.)

输入节点个数和路径权重可得到任意两点之间的最短路径，放在Muti_Cost矩阵中(Input node number and weight of available paths the shortest path between any two points, on Muti_Cost matrix)