sort

这是双线性插值法的MATLAB程序，实现了图像插值方法(This is bilinear interpolation MATLAB program, realized the Image Interpolation Method)

生成白噪声信号：包括采样频率，最大和最小频率，时间长度，幅值等要求的信号。(Generated white noise signal: including sampling frequency, maximum and minimum frequency, duration, amplitude and other requirements of the signal.)

ALPS folder 2. generate_matrix.m: generates measurement matrix. 3. generate_vector.m: generates sparse vector. 4. Report_bibtex.tex: bibtex reference for citing. 5. ALPSdemo.m: demo of ALPS.

《电力电子应用技术的MAtlab仿真》一书影印版。(Power electronics simulation base on MAtlab)

该程序给出了使用梳状导频信号的OFDM系统的仿真研究，使用了LS信道估计，最后画出了误码率图(The program gives the simulation of a comb pilot signal OFDM system using the LS channel estimation, and finally draw a diagram BER)

在matlab环境中自动识别连通区域的大小,多元数据分析的主分量分析投影，实现典型相关分析。( Automatic identification in the matlab environment the size of the connected area, Principal component analysis of multivariate data analysis projection, Achieve canonical correlation analysis.)

常用优化算法的matlab实现，如德杰斯特拉，弗洛伊德等。(Matlab optimization algorithm used to achieve, such as Dejene Stella, Freud and so on.)

应用系统动力学模型，解决在一个封闭的海岛上，对两个群体：1.狐狸(FOXES)；2.啮齿动物（RODENTS）关于生态平衡的问题。详见说明。(With the use of system dynamics model, the program resolves a problem that based on the ecological balance.)

简易教程，说明了matlab环境下simulink的部分编码例子(Easy tutorial on the part of matlab simulink environment example code)

The shuffled complex evolution with principal components analysis–University of California at Irvine (SP-UCI) method is a global optimization algorithm designed for high-dimensional and complex problems. It is based on the Shuffled Complex Evolution (SCE-UA) Method (by Dr. Qingyun Duan et al.), but solves a serious problem in searching over high-dimensional spaces," population degeneration". The population degeneration problem refers to the phenomenon that, when searching over the highdimensional parameter spaces, the population of the searching particles is very likely to collapse into a subspace of the parameter space, therefore losing the capability of exploring the entire parameter space. In addition, the SP-UCI method also combines the strength of shuffled complex, the Nelder-Mead simplex, and mutinormal resampling to achieve efficient and effective high-dimensional optimization.