1DSIMPLE

简述算法在实际当中的应用以及算法的改进和延伸(Improvement and extension of applications and algorithms of the outlined algorithm in practice)

羊与狼的故事...主要实现狼进入若干羊圈后，寻找最后所有羊圈中剩余的狼和眼数目( the wolf and sheep)

贪婪算法，可以用于资源分配等许多数学问题和工程问题中(Greedy algorithm)

求解实系数方程组的高斯消去法，约当法，追赶法，分解法，平方根法，大型稀疏方程组法(Solving real coefficient equations of the main Gaussian elimination, about the law to catch up with France, large-scale sparse equations.)

PLS部分最小二乘工具箱,数值分析的EULER法，matlab编写的元胞自动机。( PLS PLS toolbox, EULER numerical analysis method, matlab prepared cellular automata.)

Do you need to gain confidence with handling numbers and formulae? Do you want a clear, step-by-step guide to the key concepts and principles of statistics? Nearly all aspects of our lives can be subject to statistical analysis. Statistics: An Introduction shows you how to interpret, analyze and present figures. Assuming minimal knowledge of maths and using examples from a wide variety of everyday contexts, this book makes often complex concepts and techniques easy to get to grips with. This new edition has been fully updated. Whether you want to understand the statistics that you are bombarded with every day or are a student or professional coming to statistics from a wide range of disciplines, Statistics: An Introduction covers it all.

说明：  matlab常用算法程序集主要用于解决插值、函数逼近、矩阵特征值计算、数值微分、数值积分、方程求根、非线性方程组求解、解线性方程组的直接法、解线性方程组的迭代法、随机数生成、特殊函数计算、常微分方程的初值等问题(Mainly solve interpolation, function approximation, matrix eigenvalue calculation, numerical differentiation, numerical integration, equation roots, nonlinear equations solving, direct methods for solving linear equations, iterative methods for solving linear equations, random number generation, special functions Calculation, initial value of ordinary differential equations, etc.)

此为基于图像配准的傅立叶变换源代码，已精心调试过，请放心使用.(This is the image registration based on the Fourier Transform source code, has been painstakingly debugging, please rest assured that use.)

based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the minimum representation error. While the importance of sparsity is much emphasized in SRC and many related works, the use of collaborative representation (CR) in SRC is ignored by most literature.

改程序用于大地电磁法的一维反演，运用波斯蒂克反演方法(Reform program for the one-dimensional inversion of magnetotelluric method, the use of the Persian Mystic inversion method)