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RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。该代码是求解RPCA的一种数值算法——Exact ALM（Exact Augmented Lagrange Multiplier）(The most basic form of the exact ALM function is [A, E] = exact_alm_rpca(D, λ), and that of the inexact ALM function is [A, E] = inexact_alm_rpca(D, λ), where D is a real matrix and λ is a positive real number. We solve the RPCA problem using the method of augmented Lagrange multipliers. The method converges Q-linearly to the optimal solution. The exact ALM algorithm is simple to implement, each iteration involves computing a partial SVD of a matrix the size of D, and converges to the true solution in a small number of iterations. The algorithm can be further speeded up by using a fast continuation technique, thereby yielding the inexact ALM algorithm.)

灰色系统的MATLAB程序：用于实现灰色预测，适合初学者。(Gray system MATLAB program: to achieve gray prediction for beginners.)

MATLAB入门教程，十分适合初学MATLAB者学习使用，内容很详细。(MATLAB Tutorial, very suitable for beginners who learn to use MATLAB, the content is very detailed.)

CDMA transciver matlab code

利用matlab编程，来实现基于提升复小波的暂态电能质量扰动的检测。(Use matlab to achieve the detection of complex wavelet based on lifting transient power quality disturbances.)

说明：  matlab程序。模拟形状记忆合金的形状记忆效应。(Matlab program. To simulate the shape memory effect of shape-memory alloy.)

Synchronous Buck Converter: This switched power supply converts a 30V DC supply into a regulated 15V DC supply. The model can be used to both size the inductance L and smoothing capacitor C, as well as to design the feedback controller. By selecting between continuous, discrete and fixed-point controllers, the impact of discretization and using limited numerical precision can be explored

C++ code for computation of the inverse matrix with dimension 3x3.

lorenz序列产生程序，自己编写的，可产生时域波形图和混沌吸引子相图。(Lorenz chaotic sequence generation process, the preparation of their own, can produce the time-domain waveform and chaotic attractor.)

Kohonen and CPANN toolbox是开发的一个MATLAB工具箱，用来对数据结构进行研究和分类。(The Kohonen and CPANN toolbox is a collection of MATLAB modules for developing Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs). These are well known neural networks aimed to the study of data structure (Kohonen Maps) and to the data classification (CPANNs). )