risk456_2

原对偶内点法的matlab程序，应用在matpower潮流计算中(Primal-dual interior point method matlab procedures used in the calculation of the trend matpower)

matlab编写的Newmark法计算多自由度体系动力问题的通用程序，很实用！(Newmark method matlab prepared multi-degree of freedom system power issues common procedures, very practical!)

用窗函数设计数字滤波器，对所给出的含有噪声的声音信号进行数字滤波处理，得到降噪的声音信号，并进行播放试听。(Digital filter design, the sound signal containing noise given digital filter processing sound signal to reduce noise and play audition.)

this ring buffer sample.

选择二进制编码，利用遗传算法计算函数的最小值(calculate function minimum with genetic algorithm)

OSCAR is an optical FFT code used to calculate the steady state optical field circulating in Fabry Perot cavities. The code can integrate non-sperical mirrors and any arbitrary input fields. Recent applications for OSCAR have been: calculation of thermal lensing effect and calculation of diffraction loss and cavity eigen modes for mesa beams. One great advantage of OSCAR is the simplicity and exibility of the code, everyone with only minimal knowl- edge of Matlab can easily modifed OSCAR code to suit specfic purposes.

采用matlab编写的二位扩展有限元的程序，主要解决断裂力学里面的裂纹和开裂问题(Two extended finite element program using matlab, solve fracture mechanics inside the crack and cracking)

地震波作用下计算地震加速度、速度、位移反应谱(Computation of seismic response spectrum)

说明：  微波光子滤波器能够实现在光域内直接对射频信号的处理,并且较易实现可调谐性和传输函数的快速重构,从而成为微波光子学的一个重要研究内容.本代码提供了一般性的结构仿真，并且还说明了切趾响应对MSSR的影响。(Microwave photon filter can process RF signal directly in optical domain, and it is easy to realize tunability and fast reconstruction of transmission function, which has become an important research content of microwave photonics. This code provides general structure simulation, and also explains the effect of toe cutting on MSSR.)

support vector classification machine ％ soft margin ％ uses "kernel.m" ％ ％ xtrain: (Ltrain,N) with Ltrain: number of points N: dimension ％ ytrain: (Ltrain,1) containing class labels (-1 or +1) ％ xrun: (Lrun,N) with Lrun: number of points N: dimension ％ atrain: alpha coefficients (from svcm_train on xtrain and ytrain) ％ btrain: offest coefficient (from svcm_train on xtrain and ytrain) ％ ％ ypred: predicted y (Lrun,1) containing class labels (-1 or +1) ％ margin: (signed) separation from the separating hyperplane (Lrun,1(support vector machine classification% s oft margin% uses "kernel.m"%% xtrain : (Ltrain, N) with Ltrain : number of points N : % ytrain dimension : (Ltrain. 1) containing class labels (-1 or 1)% xrun : (Lrun, N) with Lrun : number of points N : % atrain dimension : alpha coefficients (from svcm_train on xtrain and ytrain)% btrain : offest coefficient (from svcm_train on xtrain and ytrain)%% ypred : predicted y (Lrun. 1) containing class labels (-1 or 1)% margin : (signed) separation from the separating hyper plane (Lrun, 1)