MATLAB-SCIENTIC-COMPUTE

Simulation of A to ground fault in a transmission system in SymPowerSystems. Also attached simple program to obtain a txt file with fault voltage values from standard .mat MATLAB file.

自动控制原理的课程设计，包含有根轨迹分析、时域分析、频域分析、控制系统设计及校正的matlab程序设计及仿真实例。(Automatic Control Theory of curriculum design, contains a root locus analysis, time-domain analysis, frequency domain analysis, control system design and calibration procedures for the design and the matlab simulation.)

用Matlab从Excel中导入数据，含虚拟数据和各种导入格式(Import data from Excel into Matlab)

自适应控制方面的经典书籍，仅供学习研究参考用，不得违规(Adaptive control of classic books)

sift algorithm for detection of object even in different orientations

In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.

the folder gives information about the image forgery detection. detection is made by examining the sift and ransac features of the image. color processing is done as a preprocessing step.

主程序arma2Ddemo是对模拟图像的2DAR和ARMA参数估计。(arma2Ddemo: See and run the demo arma2Ddemo for an example of 2D AR and ARMA parameters estimation from simulated images. - sim_ar2d: generation of simulated 2D AR process. - sim_arma2d: generation of simulated 2D ARMA process. - ar2d: solves 2D yule walker to estimate AR parameters - arma2d: estimation of 2D ARMA parameters. First step: estimation of the gaussian input by inv_ar2d, Second step: linear system solution to estimates simultaneously AR and MA parameters, as explained in [1]. - inv_ar2d: first step in arma2d. Filters through inverse filter 1/AR an AR process, to generate its innovation Gaussian signal. It is used here to estimate the Gaussian noise input to the ARMA 2D process, approximating the ARMA model to a high order AR model. - poles2coeff: converts poles chosen by user to AR or MA coefficients (support function) )

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

Algorithms for Digital Image Steganography via Statistical Restoration