TetrahedronElementStiffness

说明：  模式识别分类支持向量机和和函数集，用于模式识别分类用。核函数很多(Pattern recognition and classification support vector machine and set of functions)

在Matlab环境下实现的无损编解码，代码简单易懂(In the lossless codec implementation under the environment of Matlab, the code is simple to understand)

基于MATLAB的光线反射、折射和透镜原理的仿真程序(MATLAB-based light reflection, refraction and lens theory simulation program)

可以动态调节运行环境的参数，VIhMIry参数单径或多径瑞利衰落信道仿真，有较好的参考价值，实现了对10个数字音的识别程序VelrElV条件相关分析过程的matlab方法，包括面积、周长、矩形度、伸长度。( Can dynamically adjust the parameters of the operating environment, VIhMIry parameter Single path or multipath Rayleigh fading channel simulation, There are good reference value, Realization of 10 digital audio recognition program VelrElV condition Correlation analysis process matlab method, Including the area, perimeter, rectangular, elongation.)

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

runge kutta order 12

严格耦合波法分析光栅衍射的matlab源程序(the matlab code for rigorous coupling wave analysis of diffractiong grating! )

说明：  可实现，实用，迭代法（新创新），基于改进的迭代法图像分割算法（源码）， 核心思想：先添加高斯噪声，然后新迭代分割算法，最后显示自动计算的阈值。 (Can realize, practical, the iterative method (new innovation), the iterative method based on improved image segmentation algorithm (source), core ideas: first add gaussian noise, then new iteration segmentation algorithmFinally，finally shows the threshold automatic calculation. )

详细介绍了matalb2009a与vs2008交叉编程的过程，亲自试验过的，保证有效。(Matalb2009a described in detail the process of programming and cross-vs2008, personally tested, and guaranteed effective.)

这是对音频新训好进行bch编码后通过代同滤波器的程序(This is the new audio training for good after the BCH code generation through with the procedure Filter)