LD

创建一个first order 低通模拟信号滤波器。输入为热噪音(creative a first order low pass filter, the in put is the white noise.)

在没有压电作动器的情况下，欧拉梁的振动特性及模态(Piezoelectric actuator, the the Euler beam vibration characteristics and mode)

最新版《精通Matlab与C/C++混合程序设计》（ 第三版） 刘维编著- proficient Matlab and C/C mixed Program Design (third edition）(The latest version of Mastering Matlab and C/C++ programming mix (third edition) edited by Richard- proficient Matlab and C/C mixed Program Design (third edition))

心理洞察高手。讲述洞察人的内心深处的技巧，从而学会怎样与人交际。(Master of psychological insight. Insight into people hearts about the skills to learn how to communication with people.)

thiet ke bo loc FIR dai thong, va mo phong dau vao, ra tren matlab.

这个程序是实现局放信号的产生，通过对局放信号的分析和学习，得出局放信号的matlab表示(This program is to achieve partial discharge signal generation, signal analysis released by game and learning, drawn, said PD signal matlab)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

相信大家已经注意到了，伴随着微观金融理论的发展，以随机分析为核心的数学理论 也在同步发展，并不断为金融学家们所吸收和运用，它们交织在一起，密不可分又相映生 辉②。它们相映生辉倒不要紧，但就给研究者带来了很多困难：由于微观金融学研究重点的 特殊性和复杂性（不确定性和动态性），注定以随机分析作为其主要数学工具，这无形中提 高了这一学科的门槛③。

本人精心收藏的资料，该资料对粒子群算法改进的，值得借鉴。分享给大家(I am careful collection of data, the information on the particle swarm algorithm improvement, and worth learning from. We share)

排课问题是一个有约束的、多目标的组合优化问题，并且已经被证明是一个NP完全问题。 遗传算法借鉴生物界自然选择和自然遗传机制，使用群体搜索技术，尤其是用于处理传统搜索方法难以解决的复杂的和非线性的问题。经过近40年的发展，遗传算法在理论研究和实际应用中取得了巨大的成功，本文将遗传算法用于排课问题的求解，首先讨论了排课问题中的影响因素、主要约束条件、求解目标和难点，并用数学模型完整地描述了排课问题。其次对多个模糊排课目标进行了定量分析，建立了排课优化目标空间。针对排课问题研究了染色体编码方式以及遗传算子的设计，提出了适应度函数的计算方法。最后对排课问题进行了实验。实验结果表明，其过程的目标值跟踪显示，算法稳健趋优，所得结果令人满意。(Course Scheduling problem is a constrained, multi-objective optimization problem, and has proven to be a NP complete problem. Genetic algorithms reference biosphere and the natural genetic mechanism of natural selection, using the group search technology, particularly the traditional search methods for handling complex and difficult to solve nonlinear problems. After nearly 40 years of development, the genetic algorithm in the theoretical study and practical application was a great success, this paper genetic algorithm for solving the course timetabling problem, first discussed the impact of factors in the course arrangement, the main constraints, to solve goals and difficulties, and a complete mathematical model to describe the course arrangement. Arranging multiple fuzzy goals followed by a quantitative analysis, the optimal target Arranging space. Arranging for the Study of the chromosome coding and genetic operators design, proposed fitness function is calculated. Finally, the co)