FEM

BPSK程序，完成二进制调制过程，用于仿真，初步认识MATLAB仿真过程。(BPSK program, the completion of the binary modulation process for the simulation, an initial understanding of MATLAB simulation.)

Matlab在时间序列分析中的应用，一般可以用excel实现时间序列的分析，在这里也可以用MATLAB(The application of Matlab in time series analysis, generally can use excel realize time series analysis, here you can also use Matlab)

光伏发电系统，可用于新能源发电系统的研究设计 (PV systems)

含有实验所得的滚动轴承故障数据，共振解调法用于对振动信号的故障诊断，并能准确判定故障发生的部位。(Rolling Bearing Fault contains experimental data obtained, the resonance demodulation method for fault diagnosis of vibration signals, and can accurately determine the site of the fault.)

图像处理目标识别程序 源码网上下载的 挺实用的 试试吧或许对您有用。(Imageprocess include recognized and others maybe good for you！)

runge kutta方法求解常微分方程(the Runge–Kutta methods (German pronunciation: are an important family of implicit and explicit iterative methods for the approximation of solutions of ordinary differential equations. These techniques were developed around 1900 by the German mathematicians C. Runge and M.W. Kutta.)

主成分分析法，其本质是实现高纬到低维的分析，用matlab实现的代码(Principal component analysis, by its very nature is to achieve the high latitudes to low-dimensional analysis, implemented with the matlab code)

image segmentation, new normalized cut

Amplitude modulation and demodulation using simulink and matlab.

“Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。(In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relationships between the object of interest and its local context based on a Bayesian framework, which models the statistical correlation between the low-level features (i.e., image intensity and position) from the target and its surrounding regions. The tracking problem is posed by computing a confidence map, and obtaining the best target location by maximizing an object location likelihood function. The Fast Fourier Transform is adopted for fast learning and detection in this work. Implemented in MATLAB without code optimization, the proposed tracker runs at 350 frames per second on an i7 machine. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods in terms of efficiency, accuracy and robustness.)