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benchmarks_test_pso
- 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 ver
PkgMyAntiAlias
- 一种比较好的抗锯齿算法 Add myaa.m to your path and enjoy anti-aliased professionally looking graphics in Matlab at any time. Myaa works with any kind of graphic (3-D, plots, scatterplots, ...) and even adds anti-aliasing to text, ui controls and grids. Myaa i
ukf-matlab
- 测试ukf（卡尔曼滤波器）的matlab源代码，避免ekf的截断误差，使线性化的结果更加准确。-Test ukf (Kalman filter) of the matlab source code, to avoid ekf the truncation error, so that the result of more accurate linearization.
lpc-by-matlab
- 基于matlab的lpc分析，即线性预测。分析较为全面，且测试通过。-The lpc matlab-based analysis, that is linear prediction. More comprehensive analysis and test.
SSTSLAB1001
- 空间绳系卫星的仿真软件，用matlab编写，对于从事航天工作的人员有参考价值-Simple Space Tether Simulation Laboratory (SSTSLAB) is a simulation tool for matlab/simulink, the current version is a beta version, it need more test work to make sure that the results are acceptable accura
C-CDocument
- 对混沌时间序列相空间重构C—C方法的三点不足，提出了一种基于改进的C-c方法的 确定曩优时延与嵌入窗的新算法．在关联积分计算过程中引入了权衡计算精度与速度的可调参数， 合理选择试参数，能在不严重损失估计精度的前提下，大大加快计算速度。在理论分析的基础上， 用所提出的算法对三种混沌序列进行相空间重构，仿真结果表明该算法对最优时延的选择更准确， 对最优嵌入窗的选取更可靠。-Of chaotic time series phase space reconstruction method
matlab-tutor
- This a tutorial to help you get started in Matlab. To find more details see the very helpful book Mastering MATLAB 6 by Duane Hanselman and Bruce Littlefield. Examples of Matlab code in this pamphlet are in typewriter font like this. As you read
MultiCoreSpeedTest
- MultiCore Speed Test demo. Works a comparison between multiple cores. Useful to determine if more than one processor is currently active and what would be the performance desabling one or more cores.-MultiCore Speed Test demo. Works as a comparison b
quadetest
- Dana Quade in 1979 proposed a test that is often more powerful than the Friedman test. It also eliminates block differences but weights the raw data indicate possibly more marked treatment effects. Whereas the Friedman test is basically an extension
cut_sample
- 使用二分法对样本集进行剪辑，剪辑法的思想，就是将样本集分成训练集与考试集， 利用训练集样本对考试集的样本进行分类（使用近邻法），如果考试集中某个样本分类错误的话，将这个样本删除。在该函数中，使用最近邻法，只进行一次剪辑（遍历完考试集中的样本以后退出）。还有一种重复剪辑法（适用于样本比较多的情况），把样本随机分为多个样本集，将相邻的两个样本前一个作为考试集，后一个作为训练集，调用二分剪辑。所有的样本子集剪辑完毕以后，在递归调用，直到没有样本被剪辑掉,没得讲，重复剪辑的效果肯定好一些。 -Th
tcm_psk
- 用MATLAB程序实现了tcm_8psk的中频调制解调，有性能检测以及加入了非线性因素，很详细，毕设用的程序，比较实用。-Using MATLAB program implements tcm_8psk IF modulation and demodulation, a performance test and joined the non-linear factors, very detailed, complete set with the procedure more practical.
WiMAX_Test_4
- 这是一个用matlab里面的simulink编写的一个wimax的链路，里面有很直观的链路图，可以对wimax有一个更为直观的理解。-This is a simulink with matlab written inside a wimax link, there are very intuitive link diagram, wimax can have a more intuitive understanding.
apple
- 根据静态苹果图像RGB三值检测苹果表面是否有缺陷，比较准确-Apple RGB image from the static three-valued test whether apple surface defects, more accurate
randtest
- Matlab的序列测试程序，有好多测试，比较实用。-Sequence test program Matlab, there are a lot of testing, more practical.
oscsend
- 发送一个开放声音控制（OSC）的信息通过UDP连接 oscsend（美，路径） oscsend（美，路径，类型，arg1的，arg2的,...) oscsedn（美，路径，类型，[参数]） ü= UDP的对象与打开的连接。 路径=路径字符串 =同类型的参数类型的字符串， 支持： 我=整数 f=浮动 商S =串 每组空（忽略相应的参数） 余=脉冲（忽略相应的参数） T=真（忽略相应的参数） F=假（忽略
lab02
- 在MATLAB实现的用C实现的KNN算法，输入训练数据文件，和test文件，进行预测分类，并且可以与真实情况比较测试预测正确百分比-Implemented in MATLAB KNN algorithm implemented in C, the input training data file, and test files, to predict the classification and testing with the real situation is more correct pe
basic-pso
- 基本粒子群算法的matlab实现，粒子群是二维的，其中已给出多个测试函数。-Particle swarm optimization matlab implementation, PSO is a two-dimensional, which has given more than one test function.
test
- GMM的matalab实现，通过对多个语种进行训练，然后得出每个语种的GMM模型，最终用于语种识别-GMM' s matalab achieved through training of more than one language, then come to the GMM model for each language, and ultimately for identifying languages
kalman-test
- 通过此卡尔曼滤波，可获得比较精准的载体位置，速度，加速度等信息。-Through the kalman filter, can get a more accurate carrier position, velocity, acceleration and other information.
test
- function mean = ml_mean(data) Calculate the maximum likelihood estimation of the mean Written by Christiaan M. van der Walt Meraka Institute More resources available at http://www.patternrecognition.co.za Reference: C.M. van d