household-givens

模拟一群鸟捕食的情景，从而达到优化目标函数的目的，这就是粒子群算法！起初在可行的空间中随机的产生一群粒子，然后让每个粒子开始在虚拟的空间中向四面八方飞翔，并且每个粒子都记下他们飞过的适应值（也就是目标优化函数）最高的点，而且整个粒子群有一个最高适应值个体，这样，粒子在飞翔的时候尽量朝向自己曾飞过的最好的点和集体的最好的点。最后达到收敛到近似最优点的目的。 (Simulation of a group of birds preying on the scene, so as to achieve the purpose of optimizing the objective function, that is, PSO! At first, where feasible, have a space in a group of random particles, and then let the beginning of each particle in a virtual space to fly in all directions, and each particle they have in mind over the fitness value (that is objective optimization function) the highest point , and the whole particle swarm adaptation has a maximum value of the individual, so that particles in the fly when he had flown as far as possible towards the best point and collective best point. Finally reaching the merits of convergence to approximate most purposes.)

hysys and matlab link

CLASSIFICATION OF DATA RELATED EEG BASED SIGNAL ANALYSIS AND FEATURE EXTRACTION TECCHNIQUE

数值计算中机器精度的确定算法 MATLAB源程序 自带注释(machine precision)

Simpson Rule Algo7-2.c C program for implementing Algorithm 7.2 Algorithm translated to C by: Dr. Norman Fahrer IBM and Macintosh verification by: Daniel Mathews NUMERICAL METHODS: C Programs, (c) John H. Mathews 1995 To accompany the text: NUMERICAL METHODS for Mathematics, Science and Engineering, 2nd Ed, 1992 Prentice Hall, Englewood Cliffs, New Jersey, 07632, U.S.A. Prentice Hall, Inc. USA, Canada, Mexico ISBN 0-13-624990-6 Prentice Hall, International Editions: ISBN 0-13-625047-5 This free software is compliments of the author. E-mail address: in "mathews@fullerton.edu" Algorithm 7.2 (Composite Simpson Rule). Section 7.2, Composite Trapezoidal and Simpson s Rule, Page 365

求解输入矩阵的阶梯形式，仅供大家学习交流(Input matrix form for solving the ladder, only for them to learn from the exchange)

结构阵型分解方法matlaB程序，求解结构动力学响应(Structure formation decomposition matlaB procedures for solving structural dynamics response)

基于CV模型的matlab程序，简单，易于入门(matlab code for kalman filter(based on CV module))

对OFDM的载波频偏进行估计和补偿，采用ML最大似然估计算法，有不同频偏值和不同信噪比的仿真结果图。(For OFDM carrier frequency offset estimation and compensation, using ML maximum likelihood estimation, have different values and different SNR offset simulation results shown in Fig.)

MATLAB基础与应用书籍，学好基础，掌握未来。(Foundation and Application of matlab)