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pld程序，学习一下，希望对各位大侠有用(pld program, learning about, hope you heroes helpful)

本人精心收集的正弦内插算法，根据此算法,每个周期2.5采样点就可以重构一个正弦波形，经改造可用于VC和matlab(I carefully collected the sine interpolation algorithm, based on this algorithm, each cycle of 2.5 sampling points can reconstruct a sine wave-shaped, can be used by the transformation of VC and matlab)

this program simulates 1D electromagnetic Maxwell equations "propagation in different media", by using finite difference time domain method FDTD

说明：  供入门者使用的遗传算法程序，每个程序有详细的解释和说明，对刚步入研究生阶段的工科生有很好的帮助(A genetic algorithm program for beginners to use, each program has a detailed explanation and description, there is a good help for just entering the postgraduate students)

源码-一个实例搞定MATLAB界面编程_简单易懂适合新手。(Source- an instance to get MATLAB programming interface _ easy to understand for novice.)

说明：  这个是KPCA核主成分分析的代码，好用，里面也带有范例(This is the KPCA kernel principal component analysis code, which is easy to use and also contains examples.)

蒙特卡罗法的MATLAB源程序、MATLAB例程。(MATLAB source code of the Monte Carlo method, MATLAB routines.)

说明：  用MATLAB求解遗传算法的旅行商问题，这一类问题在大学生以及研究生的数模竞赛以及日常生活当中尤为重要的，为我们所重视。、近年来，学术界对旅行商问题也逐渐重视起来。(Using MATLAB genetic algorithm for solving the traveling salesman problem, this kind of problem students and graduate students in Mathematical Modeling Contest, and daily life is particularly important for our attention. In recent years, the academic community on the traveling salesman problem is gradually pay attention to it.)

一种matlab的重要支撑软件，适用于学习 研究的功效。(An important support software matlab, applicable to the study of the efficacy of learning.)

Multiple kernel learning is a model to merge multiple kernels by linear combination. Mostly solving the models are slow due to explicit computation of kernels. Here, we propose to approximate kernel map function explicitly in finite dimensional space. Then, we use dual coordinate descent to solve the SVM. By storing the solutions in primal, we do not have to compute the kernel explicitly. A group lasso regularization on kernel weights is solved with SVM alternatingly. This is a side-project in my research projects with Dr. Yi-Ren Yeh and Dr. Frank Wang in Academia Sinica.