m_series

Balanced PSO,可作为benchmark比较(You campare your algorithm with it.)

简单介绍了模糊控制器的隶属度函数的matlab代码输入(A brief introduction to the fuzzy controller matlab code input membership function)

一种重要的辨识方法，主要用于对电力系统中低频振荡和其他运行方式的辨识(An important recognition method, mainly used for the identification of low-frequency oscillations in the power system and other running)

Embedded Application using Matlab

说明：  matlab中对于语音编码的叙述和代码演示(matlab for speech coding in the description and code demo)

说明：  按FPE定阶的 源程序：fpe.cpp M序列：M序列.txt 白噪声：Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数，再用fpe方法判断模型的阶次。 程序运行结果如下： n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出，当n=5时，fpe值最小，所以这时的模型阶次和参数估计值为最优结果： 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)

模糊聚类分析的matlab程序，先将原矩阵标准化，再标定并生成模糊相似矩阵，最后生成动态分类图。(Matlab fuzzy clustering analysis program, the first of the original matrix standardized, re-calibration and generate fuzzy similarity matrix, and finally generate dynamic classification map.)

wsn经典路由算法，对于初学者很有借鉴意义(Classic WSN routing algorithm for beginners is of great significance)

工程师和科学家们面临着用更少的时间建立复杂系统模型的需求，他们使用分布式和并 行计算来解决高性能计算的问题。这些分布式的环境由多处理器和多核计算机来实现。 Mathworks公司开发的分布式计算工具箱可以在多处理器计算环境中使用 MATLAB 和imulink 解决计算、数据密集型问题。可以使用该工具箱解决通过装配多个处理器包含几个单独工作单位或单个大型计算的问题。这些处理器可以驻留在一个多处理器计算机，或者，当工具箱配合 MATLAB 分布式计算引擎时，驻留在计算机集群上。(Engineers and scientists are facing with less time to build models of complex systems needs, they use distributed and parallel computing to solve the problem of high-performance computing. The distributed environment consists of multi-processor and multi-core computer to achieve. Mathworks Distributed Computing Toolbox, developed in multi-processor computing environment MATLAB and imulink solve computing, data intensive problems. You can use the toolkit to solve multiple processors by assembling several separate work units or containing a single large-scale computing problems. These processors can reside on a multi-processor computer, or, when the toolbox with MATLAB Distributed Computing Engine, it resides on a computer cluster.)

artificial intelligence