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matlab ı ı r code for pic application

说明：  cancorr的matlab程序（2）.用于信号的典型相关的分析。(cancorr the matlab program (2). the canonical correlation for the signal analysis.)

This example of AC-DC-AC converter illustrates use of Universal Bridge, Multimeter, and Powergui blocks, as well as discrete control blocks of the Extras library.(A 60 Hz, voltage source feeds a 50 Hz, 50 kW load through an AC-DC-AC converter. The 600V, 60 Hz voltage obtained at secondary of the Wye/Delta transformer is first rectified by a six pulse diode bridge. The filtered DC voltage is applied to an IGBT two-level inverter generating 50 Hz. The IGBT inverter uses Pulse Width Modulation (PWM) at a 2 kHz carrier frequency. The circuit is discretized at a sample time of 2 us)

自己编写fft2和ifft2程序并进行快速傅里叶变换试验(fft2 and ifft2)

用麦克麦考方法求解一维burgers方程的matlab代码(By Mike McCaw method for solving one-dimensional burgers equation matlab code)

多输入多输出（MIMO）的预测控制MATLAB仿真(Multiple Input Multiple Output Model Predictive Control )

CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology, including a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C.

稀疏矩阵的matlab算法，以及稀疏矩阵存储技术的介绍。(Matlab sparse matrix algorithms, and sparse matrix storage technology introduction.)

基于PSCAD建立的微型电网中的含光伏、风电的模型(PSCAD establish micro grid model with photovoltaic, wind-based)

包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波(ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation: Kalman filter Extended Kalman filter Sigma-Point Kalman filters (SPKF) Unscented Kalman filter (UKF) Central difference Kalman filter (CDKF) Square-root SPKFs Gaussian mixture SPKFs Iterated SPKF SPKF smoothers Particle filters Generic SIR particle filter Gaussian sum particle filter Sigma-point particle filter Gaussian mixture sigma-point particle filter Rao-Blackwellized particle filters The italicized algorithms above are not fully functional yet (or included in the current release), but will be in the next or future releases. The code is designed to be as general, modular and extensible as possible, while at the same time trying to be as computationally efficient as possible. It has been tested with Matlab 7.2 (R2006a). )