pso-5

国外用MATLAB编写的多维分形分析断裂结构的程序。在地质建模中有潜在用途。(A MATLAB® program based on the Hou algorithm for estimation of fractal dimension and multifractal spectrum of fractures is presented. The program performance was tested with many synthetical fractals and field data. )

在Matlab对FDTD进行仿真，并对一维，二维及三维电磁传播环境分别编写了程序(On the FDTD simulation in Matlab, and the one-dimensional, two-dimensional and three-dimensional electromagnetic propagation environment programs were prepared)

Motion estimation algorithm - three step search

PCA (Principal component analysis) is used to redraw dimension of data

本程序的性能已经达到较高水平，利用贝叶斯原理估计混合logit模型的参数，计算互信息非常有用的一组程序。( The performance of the program has reached a high level, Bayesian parameter estimation principle mixed logit model, Mutual information is useful to calculate a set of procedures.)

利用MATLAB编程解飞秒激光与物质相互作用时所用到的双温方程(solve two tempture model)

说明：  数学建模中的图论知识来研究最短路径的问题，利用Dijkstra算法matlab实现(Graph theory knowledge in mathematical modeling is used to study the shortest path problem, which is realized by using Dijkstra algorithm matlab.)

Daniel P. Palomar 2010的新作，凸优化在信号处理及通信中的应用。对于研究领域为通信理论及信号处理的学生而言，我强力推荐本书。(Daniel P. Palomar s new book published in 2010, 《convex optimization in signal processing and communications》. For the students in the areas of communication theory and signal processing, I strongly recommend this book.)

说明：  遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。(Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. It is designed and proposed according to the evolution law of organisms in nature. It is a computational model of biological evolution process simulating natural selection and genetic mechanism of Darwin's biological evolution theory. It is a method to search the optimal solution by simulating natural evolution process. The algorithm transforms the solving process of the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematical method and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, it usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.)

香农编码源程序 如：p=[0.4 0.3 0.2 0.1] shannon(p)(shannon source code)