modulate_test_qpsk

Pf粒子滤波实现的目标跟踪程序，可实现针对非高斯噪声情况下的跟踪(Pf particle filter to achieve tracking procedures, can be non-Gaussian noise for tracking cases)

说明：  本文对指纹特征点的提取，特征点的匹配，用matlab进行了实现(In this paper, the fingerprint feature points extraction, feature point matching, was realized with matlab)

说明：  粒子群算法(pso)标准测试函数验证程序。在一个m文件中包括了目前文献中用于验证的7个标准测试函数(Ackley等)、三维动态显示，粒子过分集中时打散等功能。旨在为学习和研究者pso算法的同仁提供一个功能较为完备、简单易懂的标准版本，对于初学者可以通过此程序快速的实现入门，以便将更多的精力投入到深层次的研究中去！同时愿与所有致力于此的朋友共同探讨pso算法的改进与应用方面(如多目标、动态系统等)的经验。(PSO algorithm (PSO) standard test function verification process. M in a document, including the current literature is used to validate the seven standard test function (Ackley), 3D dynamic display, and the over-concentration of particles scatters when the function. Designed for researchers to study and colleagues at the PSO algorithm to provide a more complete functional and easily understood standard version, for beginners through this program to achieve rapid entry. in order to be more energy into depth study! While willing to work with all the friends here to discuss PSO algorithm improvements and applications (such as multi-target, Dynamic systems, etc.) experience.)

通过此程序可以对通过建立偏最小二乘法和互信息偏最小二乘法两种模型来预测燃油品质，并对两种方法进行比较(This procedure can be through the establishment of mutual information and partial least squares PLS two models to predict fuel quality, and compare the two methods)

This InstructionVisitor executes the instructions that it visits on a given local variable frame and stack.

预测控制中的预测函数控制（PFC),有清晰的备注(Predictive Control in Predictive Functional Control (PFC), a clear note)

说明：   在这个分支中，主要是对标准粒子群算法的惯性因子、收敛因子（约束因子）、“认知”部分的c1，“社会”部分的c2进行变化与调节，希望获得好的效果。(In this branch, mainly to the standard particle swarm algorithm of inertial factor, convergence factor (constraints), "cognitive" part of c1, "social" part of the c2 changes and adjustment, hope to get good results.)

Function tranfer example

线性调频信号产生 带宽为240MHz 脉冲宽度为5us(Chirp signal bandwidth of 240MHz generate a pulse width of 5us)

icon menu is used to dect objects