MATLABtj

root finding by false position

This file is a literature survey of password authentication

MATLAB实现部分经典测试函数的绘制,如griewank函数、Rastrigin函数、Rosenbrock函数(pictures of some classical function)

说明：  大家好，我是建模的新手，希望大家相互交流共同提高。只是一个教程。很有用的哦。(Hello everyone, I am modeling the novice, I hope everyone together to improve mutual exchanges. Just a tutorial. Oh, very useful.)

hammer collision with a mass-spring system

采用MPI+OpenMP混合模型设计并实现光化学反应双层并行模拟算法，上层基于MPI实现节点间的原子分解并行,下层基于OpenMP实现节点内的多线程矩阵并行乘法。(With MPI+OpenMP mixed model was designed and implemented The photochemical reaction bunk parallel simulation algorithms, the upper atomic decomposition based on inter-node MPI implementations parallel, the lower based on OpenMP nodes of multithreading matrix parallel multiplication.)

LBP基本算法和各种变形文档，用matlab实现。 在本机上成功运行。(LBP basic algorithm and various modifications documents, using matlab realize. Successfully run on this machine.)

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

(cvpr12)Automatic Mitral Leaflet Tracking源代码((cvpr12)Automatic Mitral Leaflet Tracking)

Sequentielle Quadratische Optimierung fuer f(x) = Min!, g(x) >= 0, h(x) = 0 unter Regularitaetsbedingung FUNKTIONEN: gp.m, gp_g.m, restor.m, sigini.m name_f.m: Zielfunktion/Gradient name_g.m: Ungleichunen/Gradienten name_h.m: Gleichungen/Gradienten INPUT: name Name des Problems x zulaessiger Punkt als Startvektor OUTPUT: (x,y,z) Kuhn-Tucker-Punkt f = f(x) Funktionswert errorcode = 1: Max. Schrittzahl in Iteration errorcode = 2: Max. Schrittzahl in Backtracking errorcode = 3: x nicht zulaessig